Prof. Hussein Abbass

Artificial Intelligence - Autonomous Systems - Humans - Swarm - Trust

Home Research Team Facilities Teaching Services
Grants Authored Books Edited Books Journals Conference Book Chapters Editorship Invited Talks

Grants

  1. ARC Discovery (2020-2024), Machine education for trusted multi-skilled evolutionary learners, H.A. Abbass, S. Elsawah, E. Petraki, $580K. [Project Web Site]
  2. ARC Discovery (2016-2020), User-task co-adaptation for effective interactive simulation environments, H.A. Abbass, K. Merrick; KC Tan (PI); A. Bezerianos (PI), $560K. [Project Web Site]
  3. ARC Discovery (2014-2016), Challenging systems to discover vulnerabilities using computational red teaming, H.A. Abbass, $399K. [Project Web Site]
  4. Group of Eight Australia - Germany Joint Research Co-operation Scheme (2013-2014), Maximum entropy analysis of flow, transport, chemical reaction & human networks, (UNSW Australia team) Niven, R., Abbass, H. and Shafi, K., (Potsdam University Germany Team) Abel, M., Michael, S. and Kolski, P., $20K.
  5. ARC LIEF (2011), Flexible architecture high-performance computing facility for the intersect consortium of New South Wales, one of 29 CIs, $500K.
  6. ARC Linkage (2011-2013), New real-time risk indicators to improve the efficiency, environmental impact and safety of air traffic management, H.A. Abbass, C.J Lokan, G.K Aldis (PI), G.P Dunstone (PI), and R.C Butcher (PI), $315K.
  7. ARC Discovery (2009-2011), Dual Phase Evolution in Networks, D. Green and H.A. Abbass, $360K.
  8. ARC LIEF (2009), A high performance computing cluster and storage for the INTERSECT Consortium of NSW, one of 24 CIs, $500K.
  9. Eurocontrol Experimental Centre (2008-2013), Using military scenarios to assess risk in civil Air Traffic Management scenarios, H.A. Abbass, M. Copland, S. Burdiken, M. Harb and C. Lokan, Euro 167K.
  10. ARC Discovery (2006-2008), Defence and Security Risk Assessment using Agent Based Distillations, M. Barlow and H.A. Abbass, $306K.
  11. ARC Linkage International (2005), Ensembles of Collaborative Neural Networks, H.A. Abbass and X. Yao, $15K.
  12. ARC Networks (2004-2008), Research Network for a Secure Australia (RNSA), one of 50 CIs, $1,500K.
  13. ARC Networks (2004-2008), Complex Open Systems Network (COSNet) , one of 50 CIs, $1,500K.
  14. ARC Linkage (2004-2006), Scenario Driven Management in a Network Environment, D. Jarrat, T. Bossomaier, and H.A. Abbass, $513K.
  15. ARC Centre (2003-2008), The ARC Centre for Complex Systems (ACCS) , one of 13 CIs, $5,250K.
  16. ARC Network Seed Funding (2003), Australian Network on Security Technology Integration, one of 20 CIs, $20K.

Authored Books

  1. Tang J., Leu G., and Abbass H.A. (2019). Simulation and Computational Red Teaming for Problem Solving. John Wiley & Sons, ISBN-10 1119527171, ISBN-13 9781119527176.
  2. Liu J., Abbass H.A., and Tan K.C. (2018). Evolutionary Computation and Complex Networks. Springer International Publishing,  ISBN (Hard Cover) 978-3-319-59998-4, (EBook) 978-3-319-60000-0,  DOI:10.1007/978-3-319-60000-0.  .
  3. Abbass H.A. (2015). Computational Red Teaming: Risk Analytics of Big-Data-to-Decisions Intelligent Systems. Springer International Publishing Switzerland. ISBN 978-3-319-08280-6 (Hard Cover), 978-3-319-08281-3 (EBook), ISBN-10 3319082809,  DOI:10.1007/978-3-319-08281-3. 
  4. Liu J., Green D.G., Abbass H.A. (2014). Dual Phase Evolution,  Springer-Verlag, New York, ISBN 978-1-4419-8422-7 (hard cover), 978-1-4419-8423-4 (EBook), ISBN-10 1441984224,  DOI:10.1007/978-1-4419-8423-4.

Selected Edited Books

  1. Abbass H.A. and Hunjet R. (Ed. 2020). Shepherding UxVs for Human Swarm Teaming: An Artificial Intelligence Approach to Unmanned X Vehicles. Springer.  
  2. Abbass H.A., Scholz J and Reid D. (Ed., 2018). Foundations of Trusted Autonomy. Springer.  ISBN (Hard Cover) 978-3-319-64815-6 , (EBook) 978-3-319-64816-3,  DOI:10.1007/978-3-319-64816-3.  [Open Access, Click on the Title to download] 
  3. Abielmona, R., Falcon, R., Zincir-Heywood, N., and Abbass, H. (Eds) (2016). Recent Advances in Computational Intelligence in Defense and Security. Springer International Publishing. ISBN 978-3-319-26448-6 (Hard Cover), 978-3-319-26450-9 (eBook), doi:10.1007/978-3-319-26450-9. [PDF File]
  4. Abbass H.A. and Essam D.L. (Eds) Applications of Information Systems to Homeland Security and Defense, IGI publishers, USA, 2005. 
  5. Abbass H.A., Sarker R. and Newton C. (Eds) (2002) Data Mining: A Heuristic Approach, Idea Group Publishing (USA).
  6. Sarker R., Abbass H.A. and Newton C. (Eds) (2002) Heuristics and Optimisation for Knowledge Discovery, Idea Group Publishing (USA).
  7. Russell Standish, Mark Bedau and Hussein Abbass (Eds), The 8th International Conference on the Simulation and Synthesis of Living Systems, MIT-Press (USA), 2002. 

Journals

  1. Hepworth, A. J., Hussein, A., Reid, D. J., and Abbass, H. A. (2022). Swarm analytics: Designing information markers to characterise swarm systems in shepherding contexts. Adaptive Behavior, 10597123221137090.
  2. Dong, X., Garratt, M. A., Anavatti, S. G., and Abbass, H. A. (2022). Towards Real-Time Monocular Depth Estimation for Robotics: A Survey. IEEE Transactions on Intelligent Transportation Systems.
  3. Liu, J., Anavatti, S., Garratt, M., and Abbass, H. A. (2022). Modified continuous Ant Colony Optimisation for multiple Unmanned Ground Vehicle path planning. Expert Systems with Applications, 196, 116605.
  4. Dong, X., Garratt, M. A., Anavatti, S. G., and Abbass, H. A. (2022). Mobilexnet: An efficient convolutional neural network for monocular depth estimation. IEEE Transactions on Intelligent Transportation Systems, 23(11), 20134-20147.
  5. Yaxley, K. J., Reid, A., Kenworthy, C., Hossny, M., Baxter, D. P., Allworth, M. B., ... and Abbass, H. (2022). Building a Sky Shepherd for the future of agriculture. Smart Agricultural Technology, 100137. DOI:doi.org/10.1016/j.atech.2022.100137
  6. Hepworth, A. J., Baxter, D. P., and Abbass, H. A. (2022). Onto4MAT: A Swarm Shepherding Ontology for Generalized Multiagent Teaming. in IEEE Access, vol. 10, pp. 59843-59861. DOI:doi.org/10.1109/ACCESS.2022.3180032
  7. Liu, X., Kasmarik, K., and Abbass, H. (2022). Assessing Player Profiles of Achievement, Affiliation, and Power Motivation Using Electroencephalography. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52(6), 3648-3658, June 2022.
  8. El-fiqi H., Wang M., Merrick, K., Bezerianos A., Tan K.C., and Abbass, H.A. (2022). Weighted Gate Layer Autoencoders. IEEE Transactions on Cybernetics, 52(8), 7242-7253, 2022.
  9. Dam, T., Anavatti, S. G., and Abbass, H. A. (2022). Mixture of Spectral Generative Adversarial Networks for Imbalanced Hyperspectral Image Classification. IEEE Geoscience and Remote Sensing Letters, vol. 19, pp. 1-5, 2022, Art no. 5502005. DOI:doi.org/10.1109/LGRS.2020.3041864
  10. Vahidnia, S., Abbasi, A., and Abbass, H. A. (2021). Embedding-based Detection and Extraction of Research Topics from Academic Documents Using Deep Clustering. Journal of Data and Information Science, 6(3), 99-122.
  11. Abbass, H., Petraki, E., Hussein, A., McCall, F., and Elsawah, S. (2021). A model of symbiomemesis: machine education and communication as pillars for human-autonomy symbiosis. Philosophical Transactions of the Royal Society A, 379(2207), 20200364.
  12. Hepworth, A.J., Baxter, D.P., Hussein, A., Yaxley, K.J., Debie, E., and Abbass, H.A. (2021). Human-Swarm-Teaming Transparency and Trust Architecture. IEEE/CAA J. Automatica Sinica, 8(7), 1281-1295. http://www.ieee-jas.org/article/id/f6ff7250-d301-4490-9dab-edc6012c5299?pageType=en
  13. Debie, E., Raul F.R., Fidock, J., Barlow, M., Merrick, K., Anavatti, S., Garratt, M., and Abbass H.A. (2021). Multimodal Fusion for Objective Assessment of Cognitive Workload: A Review. IEEE Transactions on Cybernetics, 51(3), 1542-1555.
  14. Hussein, A., Elsawah, S., Petraki, E., and Abbass, H. A. (2021). A machine education approach to swarm decision-making in best-of-n problems. Swarm Intelligence, 1-32.
  15. Wang, M., Kasmarik, K., Bezerianos, A., Tan, K. C., and Abbass, H. (2021). On the channel density of EEG signals for reliable biometric recognition. Pattern Recognition Letters, 147, 134-141.
  16. Liu, J., Anavatti, S., Garratt, M., Tan, K. C., and Abbass, H. A. (2021). A survey, taxonomy and progress evaluation of three decades of swarm optimisation. Artificial Intelligence Review, 1-119.
  17. Liu, J., Anavatti, S., Garratt, M., and Abbass, H. A. (2021). Multi-operator continuous ant colony optimisation for real world problems. Swarm and Evolutionary Computation, 100984.
  18. Vahidnia, S., Abbasi, A., and Abbass, H. A. (2021). Embedding-based Detection and Extraction of Research Topics from Academic Documents Using Deep Clustering. Journal of Data and Information Science, 6(3), 99-122.
  19. Yaxley, K. J., Joiner, K. F., and Abbass, H. (2021). Drone approach parameters leading to lower stress sheep flocking and movement: sky shepherding. Scientific reports, 11(1), 1-9.
  20. Debie, E., El-fiqi H., Fidock, J., Barlow, M., Merrick, K., Anavatti, S., Garratt, M., and Abbass H.A. (2021). Autonomous recommender system for reconnaissance tasks using a swarm of UAVs and asynchronous shepherding. Human-Intelligent Systems Integration, 3(2), 175-186.DOI:doi.org/10.1007/s42454-020-00024-w
  21. Hussein A., El- Sawah, S., and Abbass H.A. (2020). The Reliability and Transparency Bases of Trust in Human-Swarm Interaction: Principles and Implications. Ergonomics, 63(9), 1116-1132. DOI:doi.org/10.1080/00140139.2020.1764112
  22. Hussein A., El- Sawah, S., and Abbass H.A. (2020). Trust Mediating Reliability-Reliance Relationship in Supervisory Control of Human-Swarm Interactions. Human Factors : The Journal of the Human Factors and Ergonomics Society,62(8), 1237-1248. DOI:doi.org/10.1177/0018720819879273
  23. El-Fiqi, H., Campbell, B., Elsayed, S., Perry, A., Singh, H. K., Hunjet, R., and Abbass, H. A. (2020). The Limits of Reactive Shepherding Approaches for Swarm Guidance. IEEE Access, 8, 214658-214671. DOI:doi.org/10.1109/ACCESS.2020.3037325
  24. Long, N. K., Sammut, K., Sgarioto, D., Garratt, M., and Abbass, H. A. (2020). A Comprehensive Review of Shepherding as a Bio-Inspired Swarm-Robotics Guidance Approach. IEEE Transactions on Emerging Topics in Computational Intelligence, 523 - 537. DOI:doi.org/10.1109/TETCI.2020.2992778 [Author Version]
  25. Wang M., Hu J., and Abbass H.A. (2020). BrainPrint: EEG Biometric Identification based on Analyzing Brain Connectivity Graphs. Pattern Recognition, Volume 105, September 2020, 107381. DOI:doi.org/10.1016/j.patcog.2020.107381
  26. Raul F.R., Debie, E., Fidock, J., Barlow, M., Merrick, K., Anavatti, S., Garratt, M., and Abbass H.A. (2020). Electroencephalographic Workload Indicators During Teleoperation of an Unmanned Aerial Vehicle Shepherding a Swarm of Unmanned Ground Vehicles in Contested Environments. Frontiers Neuroscience, 14:40. DOI:doi.org/10.3389/fnins.2020.00040
  27. Chica, M., Chiong, R., Ramasco J.J., and Abbass H.A. (2019). Effects of update rules on networked N-player trust game dynamics. Communications in Nonlinear Science and Numerical Simulation, 79, article 104870. DOI:doi.org/10.1016/j.cnsns.2019.104870
  28. Wang M., ElFiqi H., Hu J., and Abbass H.A. (2019). Convolutional Neural Networks Using Dynamic Functional Connectivity for EEG-based Person Identification in Diverse Human States. IEEE Transactions on Information Forensics & Security, 14(12), 3259-3272. https://ieeexplore.ieee.org/document/8716699
  29. Raul Fernandez-Rojas, Anthony Perry, Hemant Singh, Benjamin Campbell, Saber Elsayed, Robert Hunjet and Abbass H. A. (2019). Contextual Awareness in Human-Advanced-Vehicle Systems: A Survey. IEEE Access, vol. 7, pp. 33304 - 33328.[ Open Access Full Paper available for Download for Free] . DOI:doi.org/10.1109/ACCESS.2019.2902812
  30. ElFiqi H., Petraki E., and Abbass H. A. (2019). Network Motifs for Translator Stylometry Identification. PLoS ONE 14(2): e0211809. https://doi.org/10.1371/journal.pone.0211809. [ Open Access Full Paper available for Download for Free] 
  31. Abbass H.A. (2019). Social Integration of Artificial Intelligence: Functions, Automation Allocation Logic, and Human-Autonomy Trust. Cognitive Computation, 11(2), 159-171. DOI:10.1007/s12559-018-9619-0. [Open Access Full Paper available for Download for Free] 
  32. Greenwood G., Abbass H.A., and Petraki E. (2018). When is Altruistic Punishment Useful in Social Dilemmas?. BioSystems, 174, 60-62. DOI:doi.org/10.1016/j.biosystems.2018.10.015.
  33. Yang, Z., Merrick K., Jin, L. and Abbass, H.A. (2018). Hierarchical Deep Reinforcement Learning for Continuous Action Control. IEEE Transactions on Neural Networks and Learning Systems, 29(11), 5174-5184. DOI:10.1109/TNNLS.2018.2805379 [PDF File]
  34. Xuejie, L., Merrick K., and Abbass H.A. (2018). Towards Electroencephalographic Profiling of Player Motivation: A Survey. IEEE Transactions on Cognitive and Developmental Systems, 10(3), 499-513. DOI: 10.1109/TCDS.2017.2726083 [PDF File]
  35. Goh S.K., Abbass H.A., Tan K.C., Al-Mamun A., Thakor N., Bezerianos A., and Li J. (2018). Spatio-spectral Representation Learning for Electroencephalographic Gait Pattern Classification. IEEE Transactions on Neural Systems & Rehabilitation Engineering, 26(9), 1858-1867. DOI: 10.1109/TNSRE.2018.2864119
  36. Xiao M., Cai K., and Abbass H.A. (2018). Hybridized Encoding for Evolutionary Multi-objective Optimization of Air Traffic Network Flow: A Case Study on China. Transportation Research Part E, 115, 35-55, https://doi.org/10.1016/j.tre.2018.04.011.
  37. Tang, J., Leu, G. and Abbass, H.A. (2018) . Networking the Boids is More Robust Against Adversarial Learning. IEEE Transactions on Network Science and Engineering. 5(2), 141-155. DOI: 10.1109/TNSE.2017.2745108
  38. Wang, K., Bui, V., Petraki, E. and Abbass, H.A. (2018) . Human-Guided Evolutionary Story Narration. IEEE Access, vol 6, 13783-13802. DOI: 0.1109/ACCESS.2018.2797879 Open Access Full Paper available for Download for Free]
  39. Harvey, J. Merrick K., and Abbass, H.A. (2018) . Assessing Human Judgement of Computationally Generated Swarming Behaviour. Frontiers Robotics and AI, 5(13). DOI:10.3389/frobt.2018.00013 [Open Access Full Paper available for Download for Free]
  40. Keshk, M., Singh, H., and Abbass H.A. (2018) . Automatic estimation of differential evolution parameters using Hidden Markov Models. Evolutionary Intelligence, 10(3–4), 77–93. DOI: 10.1007/s12065-018-0153-5 [PDF File]
  41. Goh S.K., Abbass H.A., Tan K.C., Al-Mamun A., Wang C., Guan C. (2017) . Automatic EEG Artifact Removal Techniques by Detecting Influential Independent Components. IEEE Transactions on Emerging Topics in Computational Intelligence, 1(4), 270-279. 10.1109/TETCI.2017.2690913
  42. Wang S.L., Shafi K., Ng T.F., Lokan C., Abbass H.A. (2017) . Contrasting Human and Computational Intelligence Based Autonomous Behaviors in a Blue-Red Simulation Environment. IEEE Transactions on Emerging Topics in Computational Intelligence, 1(1), 27-40. DOI:10.1109/TETCI.2016.2641929. [Open Access Full Paper available for Download for Free]
  43. Shafi K., Abbass H.A. (2017) . A Survey of Learning Classifier Systems in Games. IEEE Computational Intelligence Magazine, 12, 42 - 55. DOI:10.1109/MCI.2016.2627670. [PDF File]
  44. Zhang B., Shafi K., and Abbass H.A. (2017) . On Benchmark Problems and Metrics for Decision Space Performance Analysis in Multi-Objective Optimization. International Journal of Computational Intelligence and Applications, 16(1), 1750006-1750024.
  45. Wang B., Merrick K., and Abbass H.A. (2017) . Co-operative Coevolutionary Neural Networks for Mining Functional Association Rules. IEEE Transactions on Neural Networks and Learning Systems, 28(6), 1331-1344, DOI:10.1109/TNNLS.2016.2536104.
  46. Gee S.B., Tan K. C., and Abbass H.A. (2017) . A Benchmark Test Suite for Dynamic Evolutionary Multiobjective Optimization. IEEE Transactions on Cybernetics, 47(2), 461-472, DOI:10.1109/TCYB.2016.2519450.
  47. Goh S. K., Abbass H. A., Tan K. C., and Al Mamun, A. (2016) . Decompositional Independent Component Analysis Using Multi-objective Optimization. Soft Computing, 20(4), 1289-1304, DOI:10.1007/s00500-015-1587-7.
  48. Abbass, H. A., Leu, G., and Merrick, K. (2016). A Review of Theoretical and Practical Challenges of Trusted Autonomy in Big Data. IEEE Access, 4, 2808-2830. DOI:10.1109/access.2016.2571058. [Open Access Full Paper available for Download for Free]
  49. Abbass H.A., Petraki E., Merrick K., Harvey J., and Barlow M. (2016). Trusted Autonomy and Cognitive Cyber Symbiosis: Open Challenges. Cognitive Computation, 8(3), 385-408. 10.1007/s12559-015-9365-5.[Open Access Full Paper available for Download for Free]
  50. Abbass H.A., Greenwood G., and Petraki E. (2016). The N-Player Trust Game and its Replicator Dynamics. IEEE Transactions on Evolutionary Computation, 20(3), 470-474,. DOI:10.1109/TEVC.2015.2484840. [PDF File]
  51. Leu, G. and Abbass, H.A. (2016). A Multi-Disciplinary Review of Knowledge Acquisition Methods: From Human to Autonomous Eliciting Agents. Knowledge-Based Systems, 105, 1-22, August. DOI:10.1016/j.knosys.2016.02.012.
  52. ElFiqi H., Petraki E., and Abbass H. A. (2016). Pairwise Comparative Classification for Translator Stylometric Analysis. ACM Transactions on Asian Language Information Processing, 16(1), Article 2 Online first, DOI:10.1145/2898997.
  53. Xin Q., Xu J.X., Tan K.C., and Abbass H. A. (2016). Adaptive Cross-Generation Differential Evolution Operators for Multi-objective Optimization. IEEE Transactions on Evolutionary Computation, 20(2), 232-244. DOI:10.1109/TEVC.2015.2433672.
  54. Ghoneim A and Abbass H.A. (2016). A Multiobjective Distance Separation Methodology to Determine Sector-Level Minimum Separation for Safe Air Traffic Scenarios. European Journal of Operational Research, 253(1), 226-240, DOI:10.1016/j.ejor.2016.02.031.
  55. Xiong, J., Leus, R., Yang, Z., and Abbass, H. A. (2016). Evolutionary multi-objective resource allocation and scheduling in the Chinese navigation satellite system project. European Journal of Operational Research, 251(2), 662-675, DOI:10.1016/j.ejor.2015.11.031
  56. Harvey J., Merrick K., and Abbass H.A.(2015). Application of chaos measures to a simplified Boids flocking model. Swarm Intelligence, vol. 9, pp. 23-41.
  57. Schiechowski M, Merrick K, Mandziuk J, and Abbass H (2015) Human Machine Cooperation Loop in Game Playing, International Journal on Advances in Intelligent Systems, vol. 8, pp. 310 - 323, https://www.thinkmind.org/index.php?view=article&articleid=intsys_v8_n34_2015_8.
  58. Abbass H.A., Jiangjun T., Ellejmi M., Kirby S. (2014). Visual and auditory reaction time for air traffic controllers using quantitative electroencephalograph (QEEG) data. Brain Informatics, no. 2198-4018.
  59. Leu G., Curtis N., and Abbass H.A. (2014). Society of Mind cognitive agent architecture applied to drivers adapting in a traffic context. Adaptive Behaviour, vol. 22, no. 2, pp. 123 - 145.
  60. Abbass H.A., Tang J., Amin R., Ellejmi M., Kirby S. (2014). The computational air traffic control brain: Computational red teaming and big data for real-time seamless brain-traffic integration. Journal of Air Traffic Control, vol. 52, no. 2, pp. 10-17.
  61. Xiong J., Liu J., Chen Y., and Abbass H.A. (2014) . A Knowledge-based Evolutionary Multi-objective Approach for Stochastic Extended Resource Investment Project Scheduling Problems. IEEE Transactions on Evolutionary Computation, vol. 18, no. 5, pp. 742 - 763.
  62. Zhao W., Alam S., Abbass H.A. (2014) . MOCCA-II: A multi-objective co-operative co-evolutionary algorithm. Applied Soft Computing, vol. 23, pp. 407-416.
  63. Nguyen L., Bui L. and Abbass H.A. (2014) . DMEA-II: the Direction-based Multi-objective Evolutionary Algorithm - II. Soft Computing, vol. 18, no. 11, pp. 2119 - 2134.
  64. Alam S., Lokan C., Aldis G., Barry S., Butcher R., and Abbass H.A. (2013) . Systemic Identification of Airspace Collision Risk Tipping points using an Evolutionary Multi-Objective Scenario-based Methodology. Transportation Research Part C, Elsevier, vol. 35, pp. 57 - 84.
  65. Shafi K. and Abbass H.A. (2013) . Evaluation of an Adaptive Genetic-Based Signature Extraction System for Network Intrusion Detection. Pattern Analysis and Applications, Springer, vol. 16, no. 4, pp. 549 - 566.
  66. Zhao W., Alam S. and Abbass H.A. (2013) . Evaluating Ground-Air Network Vulnerability in an Integrated Terminal Maneuvering Area Using Co-evolutionary Computational Red Teaming. Transportation Research Part C, Elsevier, 29(4), 32-54.
  67. Wang S., Shafi K., Lokan C., and Abbass H.A. (2013) . An agent based model to simulate and analyse behaviour under noisy and deceptive information. Adaptive Behaviour, Sage, 21(2), 96-117, 2013.
  68. Abbass HA, Tucek DC, Kirby S, and Ellejmi M (2013) . Brain Traffic Integration. Air Traffic Technology International, pp. 34 - 39.
  69. Leu G, Curtis NJ, and Abbass H (2013) . Modeling and simulation of road traffic behavior: Artificial drivers with personality and emotions. Journal of Advanced Computational Intelligence and Intelligent Informatics, vol. 17, pp. 851 – 861.
  70. Shafi K., Bender A., Zhong W., and Abbass H.A. (2012) . Spatio-Temporal Dynamics of Security Investments in an Interdependent Risk Environment. Physica A: Statistical Mechanics and its Applications, 391(20), 5004-5017
  71. Liu J., Abbass H.A., Green D.G., Zhong W. (2012) . Motif Difficulty (MD): A Novel Predictive Measure of Problem Difficulty for Evolutionary Algorithms based on Network Motifs. Evolutionary Computation, MIT Press, 20(3), 1-27.
  72. Alam S., Zhao W., Tang J., Lokan C., Ellejmi M., Kirby S. and Abbass H.A. (2012) . A Co-Evolutionary Framework for Identifying Delay Patterns in Arrival Traffic and Ground Events for Dynamic CDA Operations. Air Traffic Control Quarterly, 20(1), 47-72.
  73. Tang J., Alam S., Lokan C. and Abbass H.A. (2012) . A Multi-Objective Approach for Dynamic Airspace Sectorization Using Agent Based and Geometric Models. Transportation Research Part C, Elsevier, 21(1), 89-121.
  74. Bui V., Pham V.V., Iorio A.W., Tang J., Alam S. and Abbass H.A. (2012) . Bio-Inspired Robotics for Air Traffic Weather Information Management. The Transactions of the Institute of Measurement and Control, Sage, 34(2-3), 291-317.
  75. Bui L., Abbass H.A., Barlow M., and Bender A. (2012) . Robustness Against the Decision-Maker's Attitude to Risk in Problems with Conflicting Objectives. IEEE Transactions on Evolutionary Computation, 16(1), 1-19.
  76. Abbass H.A. and Petraki E. (2011) . The Causes for No Causation: A Computational Perspective. Information Knowledge Systems Management, IOS Press, Information, Knowledge, and Systems Management, 10 (1-4), 51-74.
  77. Liu J., Abbass H.A., Zhong W., Green D.G. (2011) . Local-Global Interaction and the Emergence of Scale-Free Networks with Community Structures. Artificial Life, MIT Press, 17(4), 263-279.
  78. Abbass H.A., Bender A., Gaidow S., and Whitbread P. (2011) . Computational Red Teaming: Past, Present and Future. IEEE Computational Intelligence Magazine, IEEE Press, Volume 6, February 2011, Pages 30-42.
  79. Alam S., Nguyen M.H., H.A. Abbass, C. Lokan, M. Ellejmi and S. Kirby (2011) . Multi-Aircraft Dynamic Continuous Descent Approach Methodology for Low Noise and Emission Guidance. AIAA Journal of Aircraft, 48(4), 1225-1237.
  80. Bui L.T., Liu J., Bender A., Barlow M., Wesolkowski S. and Abbass H.A. (2011) . DMEA: a direction-based multiobjective evolutionary algorithm. Memetic Computing, Springer-Verlag, 3(4), 271-285.
  81. Zhong W., Abbass HA, Bender A, and Liu J. (2011) . Mixed Strategy and Coevolution Dynamics in Social Networks. Physica A: Statistical Mechanics and its Applications, Elsevier, 390(2), Pages 410-417.
  82. Barbosa B.H.G, Bui L.T., Abbass H.A., Aguirre L.A. and Braga A.P. (2011) . The use of coevolution and the artificial immune system for ensemble learning. Soft Computing, 15(9), 1735-1747.
  83. Pham V.V., Tang J., Alam S., Lokan C., and Abbass H.A. (2010) . Australian Aviation Emission Inventory Development and Analysis. Environmental Modelling & Software, Elsevier, 25(12), 1738-1753.
  84. S.L. Wang, K. Shafi, C. Lokan, and H.A. Abbass (2010) . Adversarial learning: the impact of statistical sample selection techniques on neural ensembles. Evolving Systems, 1(3): 181-197.
  85. Abbass H.A., Alam S., and Bender A. (2009) . MEBRA: Multiobjective Evolutionary Based Risk Assessment. IEEE Computational Intelligence Magazine, IEEE Press, Volume 4, 29-36. [Impact factors 2.622]
  86. Quek H.Y., Tan K.C., and Abbass H.A. (2009) . Evolutionary Game Theoretic Approach for Modeling Civil Violence. IEEE Transactions on Evolutionary Computation, 13(4), Pages 1-21.
  87. Rojanavasu P., Dam H.H., Abbass H.A., Lokan C. and Pinngern O. (2009) . A Self-Organized, Distributed, and Adaptive Rule-Based Induction System. IEEE Transactions on Neural Networks, 20(3), 446-459.
  88. Quek H.Y., Tan K.C., Goh C.K., and Abbass H.A. (2009) . Evolution and incremental learning in the iterated prisoners dilemma. IEEE Transactions on Evolutionary Computation, 13(2), 303-320.
  89. Bui L., Abbass H.A., and Essam D. (2009) . Localization for Solving Noisy Multi-objective Optimization Problems. Evolutionary Computations, MIT Press, 17(3), 379-409.
  90. Alam S., Shafi K., H.A. Abbass and M. Barlow (2009) . An Ensemble Approach for Conflict Detection in Free Flight by Data Mining. Transportation Research Part C, 17(3), 298-317.
  91. Shafi K. and Abbass H.A. (2009) . An Adaptive Genetic-Based Signature Learning System for Intrusion Detection. Expert Systems with Applications, Elsevier Science, 36(10), 12036-12043.
  92. Macrossan P.E., Kinghorn B.P., and Abbass H.A. (2009) . Cyclic genotyping strategies III: Investigations into group genotyping. Journal of Animal Breeding and Genetics, 126(2), 117-126.
  93. Bui L., Abbass H.A. and Essam D. (2009) . Local Models - an Approach to Distributed Multi-objective Optimization. Computational Optimization and Application Journal, 42(1), 105-139.
  94. Abbass H.A. and Bender A. (2009) . The Pareto Operating Curve for Risk Minimization. Artificial Life and Robotics Journal, 14(4), 449-452.
  95. Bui L.T., Barlow M. and Abbass H.A. (2009). A Multiobjective Risk-based Framework for Mission Capability Planning. New Mathematics and Natural Computation, World Scientific, 5(2), pp 459-485.
  96. Shafi K., Kovacs T., Abbass H.A., and Zhu W. (2009) . Intrusion Detection with Evolutionary Learning Classifier Systems. Natural Computing, Springer, 8(1), 3-27.
  97. Badham J., Abbass H.A., and Stocker R. (2008). Parameterisation of keeling€™s network generation algorithm. Journal of Theoretical Population Biology, 74(2), 161-166.
  98. Dam H., Abbass H.A., Lokan C. and Yao X. (2008) . Negative Correlation Learning for Neural-Based Learning Classifier Systems. IEEE Transactions on Data and Knowledge Engineering, vol 20(1), 26-39.
  99. Ghoneim A., Abbass H.A. and M. Barlow (2008) . Characterizing Game Dynamics in 2-Player Strategy Games Using Network Motifs. IEEE Transactions on Systems, Man, Cybernetics, Part B, vol 38(3), 682-690.
  100. Alam S., Abbass H.A. and Barlow M. (2008) . ATOMS: Air Traffic Operations and Management Simulator. IEEE Transactions on Intelligent Transportation, vol 9(2), 209-225.
  101. Nguyen M.H., Abbass H.A. and McKay R. (2008) . Analysis of CCME: Coevolutionary Dynamics, Automatic Problem Decomposition and Regularization. IEEE Transactions on Systems, Man, Cybernetics, Part C, vol 38(1), 100-109.
  102. Bui L., Deb K., Abbass H.A. and Essam D. (2008) . Interleaving Guidance in Evolutionary Multi-objective Optimization. Journal of Computer Science and Technology, 23(1), 4463.
  103. Shafi K. and Abbass H.A. (2007) . Biologically-inspired Complex Adaptive Systems approaches to Network Intrusion Detection. Information Security Technical Reports, vol 12(4), 209-217, Elsevier Science.
  104. Yang A., Abbass H.A., and Sarker R (2006) . Characterizing Warfare in Red Teaming. IEEE Transactions on Systems, Man, Cybernetics, Part B, 36(1), 268-285.
  105. Nguyen M.H., Abbass H.A. and McKay R. (2006) . A Novel Mixture of Experts Model Based on Cooperative Coevolution. Neurocomputing, Elsevier Science, Vol 1-3, 155-163.
  106. H.A. Abbass (2006) . An economical cognitive approach for bi-objective optimization using bliss points, visualization, and interaction. Soft Computing, 10(8): 687-698 (2006)
  107. Teo J. and Abbass H.A. (2005) . Multi-objectivity and Complexity in Embodied Cognition. IEEE Transactions on Evolutionary Computation, 9(4), pp. 337-360.
  108. M.H. Nguyen, H.A. Abbass, R.I. McKay (2005) . Stopping criteria for ensemble of evolutionary artificial neural networks. Applied Soft Computing, 6(1): 100-107.
  109. Jiang QS, Sarker R, and Abbass HA, (2005) Tracking Moving Objects and the Non stationary Travelling Salesman Problem, Complexity International: An electronic journal of complex systems research, vol. 11, pp. 171 - 179.
  110. Liu B, Abbass H.A. and McKay R I (2004) . Classification Rule Discovery with Ant Colony Optimisation. IEEE Computational Intelligence Bulletin, 3(1), pp. 31-35. [Impact factors 2.622].
  111. Teo J. and Abbass H.A. (2004) . Automatic Generation of Controllers for Embodied Legged Organisms: a Pareto Evolutionary Multi-Objective Approach. Evolutionary Computations, MIT Press, 12(3), pp. 355-394.
  112. Teo J. and Abbass H.A. (2004) . Information-Theoretic Landscape Analysis of Neuro-Controlled Embodied Organisms. Neural Computing and Applications, Springer, 31(1), pp. 80-89.
  113. Shan Y, Mckay RI, Abbass HA, and Essam D (2004) Program Distribution Estimation with Grammar Models, Complexity International: An electronic journal of complex systems research, vol. 11, pp. 191 - 205.
  114. Abbass H.A. (2003) . Speeding up Back-Propagation Using Multiobjective Evolutionary Algorithms. Neural Computation, MIT Press, vol. 15, No 11, 2705-2726.
  115. Teo J. and Abbass H.A. (2003) . A True Annealing Approach to the Marriage in Honey-Bees Optimization Algorithm. The International Journal of Computational Intelligence and Applications, Volume 3, No 2, pp 199-208.
  116. McKay R. and Abbass H.A. (2003) . Artificial Life: An Introduction. The International Journal of Computational Intelligence and Applications, Volume 3, No 2, pp 143-144.
  117. Teo J. and Abbass H.A. (2003) . Search Space Difficulty of Evolutionary Neuro-Controlled Legged Robots. The International Journal of Knowledge Based and Intelligent Engineering Systems, Volume 7, No 3, 149-156.
  118. Abbass H.A., Towsey M., Kozan E. and Werf J. Van Der (2003) . Genetic Algorithms for a Large Scale Dynamic Allocation Problem. Journal of Applied System Sciences (JASS), Cambridge Press, 4(2).
  119. Abbass H.A. (2002) . An evolutionary artificial neural networks approach for Breast Cancer Diagnosis. Artificial Intelligence in Medicine, Elsevier Science, vol 25/3 pp 265-281.
  120. Abbass H.A. (2002) . An agent based approach to 3-SAT using marriage in honey-bees optimization. International Journal of Knowledge-Based and Intelligent Engineering Systems (KES) , Vol. 6, No. 2, pp. 1-8.
  121. Abbass H.A. and Sarker R. (2002) . The Pareto Differential Evolution Algorithm. International Journal on Artificial Intelligence Tools, World Scientific, vol 11, No 4, pp 531-552, 2002.
  122. Abbass H.A., Towsey M., and Finn G. (2001) . C-Net: A Method for Generating Non-deterministic and Dynamic Multivariate Decision Trees. Knowledge and Information Systems, 3(2), 184-197.
  123. McKay R. and Abbass H.A. (2001) . Anti-correlation: A Diversity Promoting Mechanisms in Ensemble Learning. The Australian Journal of Intelligent Information Processing Systems (AJIIPS) , vol 7, No 3/4, pp 139-149.
  124. Wang B.B., McKay R.I., Abbass H.A. and Barlow M. (2001) . Domain Ontology Guided Feature-Selection for Document Categorization. The Australian Journal of Intelligent Information Processing Systems (AJIIPS) , vol 7, No 3/4, pp 102-109.
  125. Abbass H.A., Wiggen G., Lakshmanan R. and Morton B. (1999) . Constraint logic programming as a paradigm for heat exchanger network retrofit. The International Journal of Computers and Chemical Engineering, supplement volume of ESCAPE-9, PP.S127-S130.
  126. Rasmy M.H. and Abbass H.A. (1991) . An interactive constraint method for solving linear programming problems. Journal of Egyptian Statistical Society, Vol. 2, July.
  127. Rasmy M.H., Abbass H.A. and Labib M.M. (1991) . A proposed criterion to select the entering variable in Simplex method. (between theory and practice). Engineering Research Bulletin, Helwan Univ., Vol. 3, March.

Conferences

  1. Dam, T., Ferdaus, M. M., Anavatti, S. G., Jayavelu, S., and Abbass, H. A. (2021, October). Does Adversarial Oversampling Help us? In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (pp. 2970-2973).
  2. Baxter, D. P., Hepworth, A. J., Joiner, K. F., and Abbass, H. (2022, September). On the premise of a swarm guidance ontology for human-swarm teaming. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 66, No. 1, pp. 2249-2253). Sage CA: Los Angeles, CA: SAGE Publications.
  3. Mohamed, R. E., Elsayed, S., Hunjet, R., and Abbass, H. (2021, June). A Graph-based Approach for Shepherding Swarms with Limited Sensing Range. In 2021 IEEE Congress on Evolutionary Computation (CEC) (pp. 2315-2322). IEEE.
  4. Dam, T., Ferdaus, M. M., Pratama, M., Anavatti, S. G., Jayavelu, S., and Abbass, H. (2022, October). Latent Preserving Generative Adversarial Network for Imbalance classification. In 2022 IEEE International Conference on Image Processing (ICIP) (pp. 3712-3716). IEEE.
  5. Campbell, B., El-Fiqi, H., Hunjet, R., andAbbass, H. (2021, July). Distributed multi-agent shepherding with consensus. In International Conference on Swarm Intelligence (pp. 168-181). Springer, Cham.
  6. Hussein A., Petraki E., El-Sawah S., and Abbass H.A. (2022). Autonomous Swarm Shepherding Using Curriculum-Based Reinforcement Learning. International Conference on Autonomous Agents and Multiagent Systems (AAMAS22), Auckland, NZ.
  7. Dam, T., Ferdaus, M. M., Anavatti, S. G., Jayavelu, S., and Abbass, H. A. (2021, October). Does Adversarial Oversampling Help us?. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (pp. 2970-2973).
  8. McCall, F., Hussein, A., Petraki, E., Elsawah, S., and Abbass, H. (2021, December). Towards a systematic educational framework for human-machine teaming. In 2021 IEEE International Conference on Engineering, Technology and Education (TALE) (pp. 375-382). IEEE.
  9. Liu, J., Hussein, A., Anavatti, S., Garratt, M., and Abbass, H. A. (2021, December). UGV Path Planning based on an Improved Continuous Ant Colony Optimisation Algorithm. In 2021 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 01-08). IEEE.
  10. Mohamed, R. E., Hunjet, R., Elsayed, S., and Abbass, H. (2021, November). Deep Learning For Noisy Communication System. In 2021 31st International Telecommunication Networks and Applications Conference (ITNAC) (pp. 40-47). IEEE.
  11. Mohamed, R. E., Elsayed, S., Hunjet, R., and Abbass, H. (2021, June). A Graph-based Approach for Shepherding Swarms with Limited Sensing Range. In 2021 IEEE Congress on Evolutionary Computation (CEC) (pp. 2315-2322). IEEE.
  12. Simpson, J., Oosthuizen, R., Sawah, S. E., and Abbass, H. (2021). Agile, Antifragile, Artificial-Intelligence-Enabled, Command and Control. International Conference on Command and Control, USA. arXiv preprint arXiv:2109.06874.
  13. Debie, E., Singh, H., Elsayed, S., Perry, A., Hunjet, R., and Abbass, H. (2021, October). A Neuro-Evolution Approach to Shepherding Swarm Guidance in the Face of Uncertainty. In 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 2634-2641). IEEE.
  14. Campbell, B., El-Fiqi, H., Hunjet, R., and Abbass, H. (2021, July). Distributed Multi-agent Shepherding with Consensus. In International Conference on Swarm Intelligence (pp. 168-181). Springer, Cham.
  15. Francis, S., Anavatti, S. G., Garratt, M., and Abbass, H. A. (2021). Real-Time Multi-obstacle Detection and Tracking Using a Vision Sensor for Autonomous Vehicle. In Communication and Intelligent Systems (pp. 873-883). Springer, Singapore.
  16. Hepworth, A., Yaxley, K., Baxter, D., Joiner, K., and Abbass, H. (2020). Tracking Footprints in a Swarm: Information-Theoretic and Spatial Centre of Influence Measures. IEEE Symposium Series on Computational Intelligence, Canberra, Australia.
  17. Elsayed, S., Singh, H., Debie, E., Perry, A., Campbell, B., Hunjet, R., and Abbass, H. (2020). Path Planning for Shepherding a Swarm in a Cluttered Environment using Differential Evolution. IEEE Symposium Series on Computational Intelligence, Canberra, Australia.
  18. Nguyen, H. T., Garratt, M., Bui, L. T., and Abbass, H. (2020). Disturbances in influence of a shepherding agent is more impactful than sensorial noise during swarm guidance. IEEE Symposium Series on Computational Intelligence, Canberra, Australia.
  19. El-Fiqi, H., Campbell, B., Elsayed, S., Perry, A., Singh, H. K., Hunjet, R., and Abbass, H. (2020, July). A preliminary study towards an improved shepherding model. In Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion (pp. 75-76).
  20. Hussein A., El-Sawah S., and Abbass H.A. (2020). Swarm Collective Wisdom: A Fuzzy-Based Consensus Approach for Evaluating Agents Confidence in Global States. IEEE International Confernce on Fuzzy Systems (FUZZ-IEEE 2020), Glasgow, UK.
  21. Nguyen T., Liu J., Nguyen H., Kasmarik K., Anavatti S., Garratt M., and Abbass, H.A. (2020). Perceptron-Learning for Scalable and Transparent Dynamic Formation in Swarm-on-Swarm Shepherding. Joint International Conference on Neural Networks (IJCNN 2020), Glasgow, UK.
  22. Hussein A., El-Sawah S., and Abbass H.A. (2020). Towards Trust-Aware Human-Automation Interaction: An Overview of the Potential of Computational Trust Models . 53rd Hawaii International Conference on System Sciences (HICSS-53), Hawaii, USA.
  23. Vahidnia, S., Abbasi, A., and Abbass, H. A. (2020). A Framework for Understanding the Dynamics of Science: A Case Study on AI. Procedia Computer Science, 177, 581-586.
  24. Vahidnia, S., Abbasi, A., and Abbass, H. A. (2020). Document Clustering and Labeling for Research Trend Extraction and Evolution Mapping. EEKE 2020 - Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents, Wuhan, China.
  25. Abbass H., El-Sawah S., Petraki E., and Hunjet R. (2019). Machine Education: Designing Semantically Ordered and Ontologically Guided Transparent and Explainable Modular Neural Networks. IEEE Symposium Series on Computational Intelligence, (IEEE SSCI19), Xiamen, China.
  26. Nguyen H., Garratt M., Bui L., Abbass, H.A. (2019). Apprenticeship Learning for Continuous State Spaces and Actions in a Swarm-Guidance Shepherding Task. IEEE Symposium Series on Computational Intelligence, (IEEE SSCI19), Xiamen, China.
  27. Wade H., and Abbass H.A. (2019). Cyber-Shepherd: A Smartphone-based Game for Human and Autonomous Swarm Control. IEEE Systems, Man, Cybernetics Conference, Bari, Italy.
  28. Hussein A., El-Sawah S., and Abbass H.A. (2019). Investigating Gender Differences in Human Interactions with a Transparent Swarm. Human Factors and Ergonomics Society's 2019 International Annual Meeting, Seattle, Washington, USA. pp. 853 - 857.
  29. Hussein A., El-Sawah S., and Abbass H.A. (2019). A System Dynamics Model for Human Trust in Automation under Speed and Accuracy Requirements. Human Factors and Ergonomics Society's 2019 International Annual Meeting, Seattle, Washington, USA.
  30. Gee A. and Abbass H.A. (2019).Transparent Machine Education of Neural Networks for Swarm Shepherding Using Curriculum Design. International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary.
  31. Clayton N. and Abbass H.A. (2019).Machine Teaching in Hierarchical Genetic Reinforcement Learning: Curriculum Design of Reward Functions for Swarm Shepherding. IEEE Congress on Evolutionary Computation, Wellington, New Zealand.
  32. Singh H., Campbell B., Elsayed S., Perry A., Huntjet R. and Abbass H.A. (2019). Modulation of Force Vectors for Effective Shepherding of a Swarm: A Bi-Objective Approach. IEEE Congress on Evolutionary Computation, Wellington, New Zealand.
  33. Tang J., Alam S., and Abbass H.A. (2019). An Airspace Collision Risk Simulator for Safety Assessment. Winter Simulation ConferenceNational Harbor, Maryland, USA.
  34. El-Fiqi H., Kasmarik K., Bezerianos A., Tan K.C., and Abbass H.A. (2019). Gate-Layer Autoencoders with Application to Incomplete EEG Signal Recovery. International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary.
  35. El-Fiqi H., Wang M., Salimi N., Kasmarik K., Barlow M., and Abbass H.A. (2018). Convolution Neural Networks for Person Identification and Verification Using Steady State Visual Evoked Potential. IEEE Systems, Man, and Cybernetics Conference, Miyazaki, Japan.
  36. Wang M., Hussein A., Rojas R., Shafi K., and Abbass H.A. (2018). EEG-Based Neural Correlates of Trust in Human-Autonomy Interaction. IEEE Symposium Series on Computational Intelligence, Bengaluru, India.
  37. Hussein A., and Abbass H.A. (2018). Mixed Initiative Systems for Human-Swarm Interaction: Opportunities and Challenges. [File-Download] IEEE Annual Systems Modelling Conference, Canberra, Australia.
  38. Nguyen H., Tran P.V., Nguyen D.T., Garratt M., Kasmarik K., Barlow M., Anavatti S., Abbass, H.A. (2018). Apprenticeship Bootstrapping via Deep Learning with a Safety Net for UAV-UGV Interaction. AAAI Fall Symposium Series, Interactive Learning in Artificial Intelligence for Human-Robot Interaction Symposium (AI-HRI 18), Arlington, Virginia, USA.
  39. Greenwood G., Abbass H.A., and E. Petraki (2018). A Critical Analysis of Punishment in Public Goods Games. IEEE Computational Intelligence in Games (CIG18), Maastricht, the Netherlands.
  40. Nguyen H., Garratt M., Bui L., Abbass, H.A. (2018). Apprenticeship Bootstrapping: Inverse Reinforcement Learning in Multi-Skill UAV-UGV Tracking Task. International Conference on Autonomous Agents and Multiagent Systems (AAMAS18), Stockholm, Sweden.
  41. Wang M., Hu J., Abbass, H.A. (2018). Multi-scale Weighted Inherent Fuzzy Entropy for EEG Biomarkers. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2018), Rio de Janeiro, Brazil.
  42. Nguyen H., Garratt M., Bui L., Abbass, H.A. (2018). Apprenticeship Bootstrapping. Joint International Conference on Neural Networks (IJCNN18) , Rio de Janeiro, Brazil.
  43. Nguyen T., Nguyen H., Debbie E., Kasmarik K., Garratt M., Abbass, H.A. (2018). Swarm Q-Learning With Knowledge Sharing Within Environments for Formation Control. Joint International Conference on Neural Networks (IJCNN18), Rio de Janeiro, Brazil.
  44. Yang, Z., Merrick, K., Abbass, H.A., Jin, L. (2017). Multi-task deep reinforcement learning for continuous action control. [File-Download] International Joint Conference on Artificial Intelligence (IJCAI17), Melbourne, Australia.
  45. Nguyen H., Garratt M., Bui L., Abbass, H.A. (2017). Supervised deep actor network for imitation learning in a Ground-Air UAV-UGVs coordination task. IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2017), Hawaii, USA.
  46. Hossain M., Alam S., Abbass H. (2017). A dynamic multi-commodity flow optimization algorithm for estimating airport network capacity. In Air Traffic Management and Systems II, Lecture Notes in Electrical Engineering, vol. 420, 420: 205-220.
  47. Greenwood G., Abbass H.A., and Petraki E. (2017). Emotion, trustworthiness and altruistic punishment in a tragedy of the commons social dilemma. Lecture Notes Artificial Intelligence, 10142, Springe-Verlag, 12-24.
  48. Zhang B., Shafi K., Abbass H.A. (2016). Hybrid knowledge-based evolutionary many-objective optimization. IEEE Congress on Evolutionary Computation, 1007-1014.
  49. Goh S.K., Abbass H.A., Tan K.C., Al-Mamun A., Guan C., Wang C.C. (2016). Multiway analysis of EEG artifacts based on Block Term Decomposition. Proceedings of the International Joint Conference on Neural Networks. 2016-October: 913-920.
  50. Tang J., Petraki E., Abbass H.A. (2016). Shaping Influence and Influencing Shaping: A Computational Red Teaming Trust-based Swarm Intelligence Model. International Conference on Swarm Intelligence, Bali, Indonesia, Springer International Publishing. 9712: 14-23. [Awarded Best Paper]
  51. Abdelfattah S., Merrick K., Abbass H .A. (2016). Theta-Beta Ratios Are Prominent EEG Features for Visual Tracking Tasks. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 60, No. 1, pp. 21-25). SAGE Publications.
  52. Abdelfattah S; Merrick K; Abbass H (2016). Eye Movements as Information Markers in EEG Data. IEEE Symposium Series on Computational Intelligence, Athens, Greece, presented at IEEE Symposium Series on Computational Intelligence, Athens, Greece, 06 - 09 December 2016
  53. Dunk I; Abbass H (2016). Emergence of Autonomy in Leader-Follower Boids-Inspired Systems. IEEE Symposium Series on Computational Intelligence, Athens, Greece, presented at IEEE Symposium Series on Computational Intelligence, Athens, Greece, 06 - 09 December 2016
  54. Wang M; Abbass H; Hu J (2016). Continuous Authentication Using EEG and Face Images for Trusted Autonomous Systems. The 2016 Privacy, Security and Trust Fourteenth Annual Conference, Auckland, New Zealand, 12 - 14 December 2016
  55. Liu X; Merrick K; Abbass H (2016). Designing Artificial Agents to Detect the Motive Profile of Users in Virtual Worlds and Games. IEEE Symposium Series on Computational Intelligence, Athens, Greece, presented at IEEE Symposium Series on Computational Intelligence, Athens, Greece, 06 - 09 December 2016
  56. Wang M; Abbass H; Hu J; Merrick K (2016). Detecting Rare Visual and Auditory Events from EEG Using Pairwise-Comparison Neural Networks. The 8th International Conference on Brain-Inspired Cognitive Systems, China, presented at The 8th International Conference on Brain-Inspired Cognitive Systems, China, 01 - 01 January 2016
  57. Greenwood G., Abbass H.A., and Petraki E. (2016). Finite Population Trust Game Replicators. Australasian Conference on Artificial Life and Computational Intelligence, LNAI 9592, Springe-Verlag, pp. 324 - 335, 10.1007/978-3-319-28270-1_27.
  58. Leu, G., & Abbass, H. (2016). Computational Red Teaming in a Sudoku Solving Context: Neural Network Based Skill Representation and Acquisition. In Intelligent and Evolutionary Systems (pp. 319-332). Springer International Publishing.
  59. Harvey J; Merrick K; Abbass H (2016). Quantifying Swarming Behaviour. The Seventh International Conference on Swarm Intelligence, Indonesia, presented at The Seventh International Conference on Swarm Intelligence, Indonesia, 01 - 01 January 2016
  60. Abbass H.A. and Young L. (2015). From System Thinking to Capability Thinking using the Thinking Capability Analysis Technique. MODSIM.
  61. Al-Ani, A., Naik, G. R., & Abbass, H. A. (2015, November). A Methodology for Synthesizing Interdependent Multichannel EEG Data with a Comparison Among Three Blind Source Separation Techniques. In Neural Information Processing (pp. 154-161). Springer International Publishing.
  62. Goh, S. K., Abbass, H. A., Tan, K. C., & Al Mamun, A. (2015). Evolutionary Big Optimization (BigOpt) of Signals. IEEE CEC, Japan.
  63. Wang B., Merrick K. and Abbass H.A. (2015). Autonomous Hypothesis Generation as Environment Learning Mechanism for Agent Design. LNCS 8955, Springer, 210-225.
  64. Abbass, H. A., Tang, J., Amin, R., Ellejmi, M., & Kirby, S. (2014, September). Augmented cognition using real-time EEG-based adaptive strategies for air traffic control. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 58, No. 1, pp. 230-234). SAGE Publications.
  65. Petraki E. and Abbass H.A. (2014). On Trust and Influence: A Computational Red Teaming Game Theoretic Perspective. IEEE Computational Intelligence in Defence and Security Symposium, Hanoi, December 2014.[PDF File]
  66. Rafael Falcon, Rami Abielmona, Sean Billings, Alex Plachkov and Hussein Abbass (2014). Risk Management with Hard-Soft Data Fusion in Maritime Domain Awareness. IEEE Computational Intelligence in Defence and Security Symposium, Hanoi, December 2014.
  67. Abbass, H. A. (2014). Calibrating independent component analysis with laplacian reference for real-time EEG artifact removal. LNCS 8836, Springer, 68-75.
  68. Goh, S. K., Abbass, H. A., Tan, K. C., & Al Mamun, A. (2014). Artifact Removal from EEG Using a Multi-objective Independent Component Analysis Model. LNCS 8834, Springer, 570-577.
  69. Leu G., Tang J., and Abbass H.A. (2014). On the role of working memory in trading-off skills and situation awareness in Sudoku. LNCS 8836, Springer, 571-578.
  70. Ren, S., Tang, J., Barlow, M., & Abbass, H. A. (2014, July). An interactive evolutionary computation framework controlled via EEG signals. In Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on (pp. 2402-2409). IEEE.
  71. Tang J. & Abbass H.A. (2014). Learning the Behavior of Aircraft Landing Sequencing using a Society of Probabilistic Finite State Machines. IEEE WCCI, Beijing, China, pp. 610-617.
  72. Amin R., Tang J., Ellejmiy M., Kirbyy S., and Abbass H.A. (2014). Trading-off Simulation Fidelity and Optimization Accuracy in Air-Traffic Experiments using Differential Evolution. IEEE WCCI, Beijing, China, pp. 475-482.
  73. Zhang B., Shafi K., and Abbass H.A. (2014). Online Knowledge-based Evolutionary Multi-Objective Optimization. pp. IEEE WCCI, Beijing, China, pp. 2222-2229.
  74. Rubai A., Tang J., Ellejmi M., Kirby S., and Abbass H.A. (2013). Computational Red Teaming for Correction of Traffic Events in Real Time Human Performance Studies. USA/Europe ATM R&D Seminar, Chicago, IL, USA,2013
  75. Nguyen L., Bui L. and Abbass H.A (2013). A New Niching Method for the Direction-based Multi-objective Evolutionary Algorithm. IEEE Symposium Series on Computational Intelligence, Singapore.
  76. Alam S., Hossain M., Lokan C., Barry S., Aldis G., Butcher R. and Abbass H.A. (2013). Real Time Prediction of Worst Case Air Traffic Sector Collision Risk using Evolutionary Optimization. IEEE Symposium Series on Computational Intelligence, Singapore.
  77. Amin R., Tang J., Ellejmi M., Kirby S. and Abbass H.A. (2013). An Evolutionary Goal-Programming Approach Towards Scenario Design for Air-Traffic Human-Performance Experiments. IEEE Symposium Series on Computational Intelligence, Singapore.
  78. Ghoneim, Ahmed, Garrison W. Greenwood, and Hussein Abbass. (2013). Distributing cognitive resources in one-against-many strategy games. IEEE Congress on Evolutionary Computation (CEC), 1387-1394. IEEE.
  79. Leu G., Curtis N., and Abbass H.A. (2012). Modeling and Evolving Human Behaviors and Emotions in Road Traffic Networks. Procedia Social and Behavioral Sciences, Elsevier, Vol 54, 999-1009.
  80. Ren S., Barlow M., and Abbass H.A. (2012). Frontal Cortex Neural Activities Shift Cognitive Resources Away from Facial Activities. 19th International Conference on Neural Information Processing (ICONIP2012), LNCS766, 132-139, Springer.
  81. Mount W., Tucek D. and Abbass H.A. (2012). A Psychophysiological Analysis of Weak Annoyances in Human Computer Interfaces. 19th International Conference on Neural Information Processing (ICONIP2012), LNCS7663, 202-209, Springer.
  82. Tucek D., Mount W. and Abbass H.A. (2012). Neural and Speech Indicators of Cognitive Load for Sudoku Game Interfaces. 19th International Conference on Neural Information Processing (ICONIP2012), LNCS7663, 210-217, Springer.
  83. Mount W., Tucek D. and Abbass H.A. (2012). Psychophysiological Evaluation of Task Complexity and Cognitive Performance in a Human Computer Interface Experiment. 19th International Conference on Neural Information Processing (ICONIP2012), LNCS7663, 600-607, Springer.
  84. Zhang B., Shafi K., and Abbass H.A. (2012). Density Based Multi-Objective Optimization for Smart Distribution Grid Design. Ninth International Conference on Simulated Evolution and Learning (SEAL2012), LNCS, Springer.
  85. Wang B., Merrick K.E., Abbass H.A. (2012). Developing Attention Focus Metrics for Autonomous Hypotheses Generation in Data Mining. Ninth International Conference on Simulated Evolution and Learning (SEAL2012), LNCS, Springer.
  86. Shafi K., Bender A., and Abbass H.A. (2012). Multi Objective Learning Classifier Systems Based Hyperheuristics for Modularised Fleet Mix Problem. Ninth International Conference on Simulated Evolution and Learning (SEAL2012), LNCS, Springer.
  87. Vu C.C., Bui L.T., and Abbass H.A. (2012). DEAL: A Direction-guided Evolutionary Algorithm. Ninth International Conference on Simulated Evolution and Learning (SEAL2012), LNCS, Springer.
  88. Wang K., Bui V., Petraki E., and Abbass H.A. (2012). From subjective to objective metrics for evolutionary story narration using event permutations. Ninth International Conference on Simulated Evolution and Learning (SEAL2012), LNCS, Springer.
  89. Alam S., Lokan C., and Abbass H.A. (2012). What can make an airspace unsafe? Characterizing collision risk using multi-objective optimization. IEEE Congress on Evolutionary Computation, Brisbane, Australia.
  90. Bui V., Bender A. and Abbass H.A. (2012). An Expressive GL-2 Grammar for Representing Story-like Scenarios. IEEE Congress on Evolutionary Computation, Brisbane, Australia.
  91. Tang J., Alam S., Lokan C. and Abbass H.A. (2012). A Multi-objective Evolutionary Method for Dynamic Airspace Re-sectorization using Sectors Clipping and Similarities. IEEE Congress on Evolutionary Computation, Brisbane, Australia.
  92. Xiong J., Shafi K. and Abbass H.A. (2012). Multi-Uncertainty Problems (MUP) with Applications to Managing Risk in Resource-Constrained Project Scheduling. IEEE Congress on Evolutionary Computation, Brisbane, Australia.
  93. Abbass H.A., W.M. Mount, D. Tucek and JP Pinheiro (2011). Towards a Code of Best Practice for Evaluating Air Traffic control Interfaces. Australian Transport Research Forum, Adelaide, Australia.
  94. Shafi K., Bender A., and Abbass H.A. (2011). Fleet Estimation for Defence Logistics Using a Multi-Objective Learning Classifier System. Genetic and Evolutionary Computation Conference, Dublin, Ireland, ACM Press.
  95. El-Fiqi H., Petraki E., and Abbass H.A. (2011). A Computational Linguistic Approach for the Identification of Translator Stylometry using Arabic-English Text. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Taiwan.
  96. Xiong J., Liu J., Chen Y., and Abbass H.A. (2011). An Evolutionary Multi-objective Scenario-Based Approach for Stochastic Resource Investment Project Scheduling. IEEE Congress on Evolutionary Computation (IEEE-CEC), New Orleans, USA.
  97. Bui L.T., Abbass H.A., Baker S., Barlow M., Bender A., and Saker R. (2011). Grid-Based Heuristic for Two-Dimensional Packing Problems. IEEE Congress on Evolutionary Computation (IEEE-CEC), New Orleans, USA.
  98. Ghoneim A., Essam D., and Abbass H.A. (2011). On Computations and Strategies for Real and Artificial Systems. European Conference on Artificial Life, Paris, August 8-12.
  99. Alam S., Zhao W., Tang J., Lokan C., Abbass H.A., Ellejmi M. and Kirby S. (2011). Discovering Delay Patterns in Arrival Traffic with Dynamic Continuous Descent Approaches using Co-Evolutionary Red Teaming. 9th USA/EUROPE Air Traffic Management Research & Development Seminar (ATM R&D Seminar), Berlin, Germany, June 2011. [Awarded Best Paper, Ground-Air Track]
  100. Ghoneim A., Essam D., and Abbass H.A. (2011). Competency Awareness in Strategic Decision Making. IEEE Conference on Cognitive Methods in Situation Awareness and Decision Support, Florida, USA, February, 2011.
  101. Leu G., Abbass H.A., and Curtis N. (2010). Resilience of ground transportation networks: A case study on Melbourne. Australian Transport Research Forum, Canberra, October.
  102. Purton L., Abbass H.A., and Alam S. (2010). Identification of ADS-B System Vulnerabilities and Threats. Australian Transport Research Forum, Canberra, October.
  103. Pham V., Bui L., Alam S., Lokan C. and Abbass H.A. (2010). A Pittsburgh Multi-Objective Classifier for User Preferred Trajectories and Flight Navigation. IEEE Congress on Evolutionary Computation, Barcelona, Spain.
  104. Shafi K., Bender A. and Abbass H.A. (2010). Evolutionary Dynamics of Interdependent Exogenous Risks. IEEE Congress on Evolutionary Computation, Barcelona, Spain.
  105. Boulden S., Iorio A. and Abbass H.A. (2010). Learning Synchronization Behaviours in Networked Complex Systems Using Genetic Algorithms. IEEE Congress on Evolutionary Computation, Barcelona, Spain
  106. Liu J., Zhong W., Abbass H.A. and Green D. (2010). Separated and Overlapping Community Detection in Complex Networks using Multiobjective Evolutionary Algorithms. IEEE Congress on Evolutionary Computation, Barcelona, Spain.
  107. Hossain M.M., Abbass H.A., Lokan C. and Alam S. (2010). Adversarial Evolution: Phase Transition in Non-uniform Hard Satisfiability Problems. IEEE Congress on Evolutionary Computation, Barcelona, Spain.
  108. Zhao W., Liu J., Abbass H.A. and Bender A. (2010). A Multi-objective Risk-Based Approach for Airlift Task Scheduling Using Stochastic Bin Packing. IEEE Congress on Evolutionary Computation, Barcelona, Spain.
  109. Bui V., Abbass H.A. and Bender A. (2010). Evolving Stories: Grammar Evolution for Automatic Plot Generation. IEEE Congress on Evolutionary Computation, Barcelona, Spain.
  110. Wang S.L., Shafi K., Lokan C. and Abbass H.A. (2010). Robustness of Neural Ensembles Against Targeted and Random Adversarial Learning. IEEE International Conference on Fuzzy Systems, Barcelona, Spain
  111. Wang K., Bui, V.Q. and Abbass, H.A. (2010). Evolving stories: Tree Adjoining Grammar Guided Genetic Programming for Complex Plot Generation. International Conference on Simulated Evolution and Learning (SEAL2010), Kanpur, India, 1-4 December.
  112. Alam S., Nguyen M.H., Abbass H.A., Lokan C., Ellejmi M., and Kirby S. (2010). A Dynamic Continuous Descent Approach Methodology for Low Noise and Emission. 29th IEEE/AIAA Digital Avionics Systems Conference, Salt Lake City, UT, USA, 3 Oct 2010. [Awarded Best Paper, Environment Track]
  113. Abbass H.A. and Petraki E. (2010). A pedagogical framework for succeeding in a cross-disciplinary PhD. International Higher Education Conference, Perth, Australia, November, 2010.
  114. Alam S., Lokan C.J., Abbass H.A., Ellejmi M., and S. Kirby (2010). An Evolutionary Computational Analysis of Tactical Controller Tool. Aviation Information Technology Engineering and Management Conference, New Orleans, Louisiana, USA, Mar 2010.
  115. Bui L.T., Wesolkowski S., Bender A., Abbass H.A. and Barlow M. (2009). A Dominance-based Stability Measure for Multi-Objective Evolutionary Algorithms. IEEE Congress on Evolutionary Computation (CEC), Norway.
  116. Bui V.Q., Bui L.T., Abbass H.A., Bender A. and Ray P. (2009). On the Role of Information Networks in Logistics: An Evolutionary Approach with Military Scenarios. IEEE Congress on Evolutionary Computation (CEC), Norway.
  117. Alam S., Tang J., Abbass H.A. and Lokan C.J. (2009). The effect of symmetry in representation on scenario-based risk assessment for air-traffic conflict resolution strategies. IEEE Congress on Evolutionary Computation (CEC), Norway.
  118. Chen K.Y., Lindsay P.A., Robinson P.J. and Abbass H.A. (2009). A Hierarchical Conflict Resolution Method for Multi-Agent Path Planning. IEEE Congress on Evolutionary Computation (CEC), Norway, 2009.
  119. Alam, S., Abbass, H.A., Lokan C.J. (2009). Computational Red Teaming to Investigate Failure Patterns in Medium Term Conflict Detection. 8th Eurocontrol Innovation Research Workshop and Conference, Eurocontrol Experiment Research Center, Paris, France.
  120. Abbass H.A., Bender A., Dam H., Baker S., Whitacre J. and Sarker R. (2008). , Computational Scenario-based Capability Planning. Genetic and Evolutionary Computation Conference (GECCO), Atlanta, Georgia, ACM Press.
  121. Whitacre J., Abbass H.A., Sarker R., Bender A. and Baker S. (2008). Strategic Positioning in Tactical Scenario Planning. Genetic and Evolutionary Computation Conference (GECCO), Atlanta, Georgia, ACM Press.
  122. Bui L.T., Whitacre J. and Abbass H.A. (2008). Performance Analysis of Elitism in Multi-objective Ant Colony Optimization Algorithms. IEEE Congress on Evolutionary Computation (CEC), Hong Kong.
  123. Barbosa B., Bui L.T., Abbass H.A., Aguirre L.A., and Braga A.P (2008). Evolving an Ensemble of Neural Networks using Artificial Immune Systems. LNCS, SEAL.
  124. Soliman O.S., Bui L. and Abbass H.A., (2007). The Effect of a Stochastic Step Length on the Performance of the Differential Evolution Algorithm. IEEE Congress on Evolutionary Computation (CEC), Singapore, 25-28 September.
  125. Shafi K., Abbass H. and Zhu W. (2007). Real Time Signature Extraction During Adaptive Rule Discovery Using UCS. IEEE Congress on Evolutionary Computation (CEC), Singapore, 25-28 September.
  126. Ghoneim A., Abbass H.A. and Barlow M. (2007). The Critical Point When Prisoners Meet the Minority: Local and Global Dynamics in Mixed Evolutionary Games. IEEE Congress on Evolutionary Computation (CEC), Singapore, 25-28 September.
  127. Ghoneim A., Abbass H.A. and Barlow M. (2007). Investigating Alliance Dynamics Using a Co-evolutionary Iterated Prisoners Dilemma with an Exit Option. IEEE Congress on Evolutionary Computation (CEC), Singapore, 25-28 September.
  128. Greenwood G. and Abbass H.A. (2007). A New Local Search Algorithm for Continuous Spaces Based on Army Ant Swarm Raids. IEEE Congress on Evolutionary Computation (CEC), Singapore, 25-28 September.
  129. Chen K.Y., Dam H., Lindsay P. and Abbass H.A. (2007). Biasing XCS with Domain Knowledge for Planning Flight Trajectories in a Moving Sector Free Flight Environment. IEEE Symposium on Artificial Life (IEEE-ALife), Honolulu, 1-4 April.
  130. Ghoneim A., Abbass H.A. and Barlow M. (2007). Rounds effect in evolutionary games. The 3rd Australian conference on Artificial Life (ACAL07), LNCS 4828, pp. 72-83, 2007.
  131. Alam S., Nguyen M.H., Abbass H.A. and Barlow M. (2007). Ants guide future pilots. The 3rd Australian conference on Artificial Life (ACAL07), LNCS 4828, pp. 36-48, 2007.
  132. Bui L.T., Soliman O. and Abbass H.A. (2007). A Modified Strategy for the Constriction Factor in Particle Swarm Optimization. The 3rd Australian conference on Artificial Life (ACAL07), LNAI 4828, 2007.
  133. Ghoneim A., Abbass H.A. and Barlow M. (2007). Information Sharing in the Iterated Prisoner Dilemma Game. IEEE Symposium on Computational Intelligence in Games (CIG), Honolulu, 1-4 April.
  134. Ziauddin U., Sarker R. and Abbass H.A. (2007). Improving the Performance of GA in CVRP using Self Imposed Constraints. IEEE Symposium on Computational Intelligence in Scheduling (CIS), Honolulu, 1-4 April.
  135. Barlow M., Yang A. and Abbass H.A. (2007). A Temporal Risk Assessment Framework for Planning A Future Force Structure. IEEE Symposium on Computational Intelligence in Defence and Security Applications (CIDSA), Honolulu, 1-4 April.
  136. Nguyen M.H., Alam S., Tang J., and Abbass H.A. (2007). Dynamic Weather Avoidance Trajectories in a Traffic Constrained Enroute Airspace. 6th Eurocontrol Innovative Research Workshop, 6th Eurocontrol Experimental Centre, France, Dec 4-6, 2007.
  137. Alam S., Shafi K., Abbass H.A., and Barlow M. (2007). Evolving Air Traffic Scenarios for the Evaluation of Conflict Detection Models. 6th Eurocontrol Innovative Research Workshop, Eurocontrol Experimental Centre, France, Dec 4-6, 2007.
  138. Goh C.K., Quek H.Y., Tan K.C., and Abbass H.A. (2006). Modeling Civil Violence: An Evolutionary Multi-Agent. Game Theoretic Approach, The IEEE Congress on Evolutionary Computation (CEC2006), Vancouver, BC, Canada, IEEE-Press, 1624-1631.
  139. Shafi K., Abbass H.A., and Zhu W. (2006). The Role of Early Stopping and Population Size in XCS for Intrusion Detection. 6th International Conference on Simulated Evolution and Learning (SEAL06), LNCS 4247, Hefei, China pp. 50-57.
  140. Yang A., Abbass H.A., and Sarker R. (2006). Land Combat Scenario Planning: A Multiobjective Approach. 6th International Conference on Simulated Evolution and Learning (SEAL06), LNCS 4247, Hefei, China, pp. 837-844
  141. Alam S., Bui L.T., Abbass H.A., and Barlow M. (2006). Pareto Meta-Heuristics for Generating Safe Flight Trajectories Under Weather Hazards. 6th International Conference on Simulated Evolution and Learning (SEAL06), LNCS 4247, Hefei, China, pp. 829-836
  142. Bui L.T., Deb K., Abbass H.A., and Essam D., (2006). Dual Guidance in Evolutionary Multi-objective Optimization By Localization. 6th International Conference on Simulated Evolution and Learning (SEAL06), LNCS 4247, Hefei, China, pp. 384-391.
  143. Bui L.T., Juergen B. and Abbass H.A. (2005). Multiobjective optimization for dynamic environments. The IEEE Congress on Evolutionary Computation (CEC), Edinburgh, UK, 2005, Vol. 3, 2349- 2356.
  144. Dam H., Abbass H.A., and Lokan C. (2005). The Performance of the DXCS System on Continuous-Valued Inputs in Stationary and Dynamic Environments. The IEEE Congress on Evolutionary Computation (CEC), Edinburgh, UK, 2005, Vol.1, 618- 625.
  145. Bui L., Abbass H.A., and Essam D. (2005). Fitness inheritance for noisy evolutionary multi-objective optimization. Genetic and Evolutionary Computation Conference (GECCO), Washington D.C., ACM Press.
  146. Bui L., Branke J., and Abbass H.A. (2005). Diversity as a selection pressure in dynamic environments. Genetic and Evolutionary Computation Conference (GECCO), Washington D.C., ACM Press.
  147. Dam H., Abbass H.A., and Lokan C. (2005). DXCS: an XCS system for distributed data mining. Genetic and Evolutionary Computation Conference (GECCO), Washington D.C., ACM Press.
  148. McPartland M., Nolfi S., and Abbass H.A. (2005). Emergence of Communication in Competitive Multi-Agent Systems: A Pareto multi-objective approach. Genetic and Evolutionary Computation Conference (GECCO), Washington D.C., ACM Press.
  149. Sastry K., Abbass H.A., Goldberg D., and Johnson D.D. (2005). Sub-structural niching in estimation distribution algorithms. Genetic and Evolutionary Computation Conference (GECCO), Washington D.C., ACM Press.
  150. Yang A., Abbass H.A. and Sarker R. (2005). WISDOM-II: A Network Centric Model for Warfare. Ninth International Conference on Knowledge-Based Intelligent Information & Engineering Systems (KES 2005), Lecture Note Computer Science LNCS 3683, Melbourne, Australia, pp. 813-819.
  151. Abbass H.A., Barlow M., Essam D., and Yubin Y. (2005). Connecting the dots to disconnect them: A study into network evolution and dynamics for analyzing terrorist networks. The International Society for Optical Engineering (SPIE), Microelectronics, MEMS, and Nanotechnology Symposium, Complex Systems Conference, Brisbane, Qld, 2005.
  152. Yang A., Abbass H.A., and Sarker R. (2005). Risk Assessment of Capability Requirements Using WISDOM-II. The International Society for Optical Engineering (SPIE), Microelectronics, MEMS, and Nanotechnology Symposium, Complex Systems Conference, Brisbane, Qld, 2005.
  153. Dam H., Shafi K. and Abbass H.A. (2005). Can evolutionary computation handle large datasets? A study into network intrusion detection. The 18th Australian Joint Conference on Artificial Intelligence, Lecture Notes in Artificial Intelligence, LNAI 3809, Springe-Verlag, pp. 1092-1095.
  154. Dam H., Abbass H.A., and Lokan C. (2005). Be Real! XCS with Continuous-Valued Inputs. The Eighth International Workshop on Learning Classifier Systems (IWLCS-2005), Washington D.C., ACM Press, 2005.
  155. Yang A., Abbass H.A. and Sarker R. (2005). Evolving Agents for Network Centric Warfare. Second Workshop on Military and Security Applications of Evolutionary Computation, Washington D.C., ACM Press, 2005.
  156. Abbass H.A. (2004). An Inexpensive Cognitive Approach for Bi-Objective Optimization Using Bliss Points and Interaction. The 8th International Conference on Parallel Problem Solving from Nature (PPSN VIII), Birmingham, Lecture Notes in Computer Science LNCS 3242, Springer-Verlag, pp. 712-721.
  157. Shan Y., McKay R.I., Baxter R., Abbass H.A., Essam D.L., and Nguyen H X. (2004). Grammar Model-based Program Evolution. Proceedings of the Congress on Evolutionary Computation, Portland, Oregon, June.
  158. Hoai N.X., McKay R.I., Essam D.L. and Abbass H.A. (2004). Towards an Alternative Comparison between Genetic Programming Systems. The 7th European Conference on Genetic Programming (EUROGP), Lecture Notes in Computer Science, LNCS 3003, Springer-Verlag, pp. 67 -77.
  159. Sastry K., Abbass H.A. and Goldberg D. (2004). Sub-Structural Niching in Non-Stationary Environments. The 17th Australian Joint Conference on Artificial Intelligence, Lecture Notes in Artificial Intelligence, LNAI 3339, Springe-Verlag, pp. 873-885.
  160. Yang A., Abbass H.A. and Sarker R. (2004). Landscape Dynamics in Multi-agent Simulation Combat Systems. The 17th Australian Joint Conference on Artificial Intelligence, Lecture Notes in Artificial Intelligence, LNAI 3339, Springer-Verlag, 39-50.
  161. Teo J., Nguyen M.H. and Abbass H.A. (2003). Multi-Objectivity as a Tool for Constructing Hierarchical Complexity. The Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2003), Chicago, Lecture Notes in Computer Science LNCS2724, Springer-Verlag, 483-494, July.
  162. Teo J. and Abbass H.A. (2003). Is a Self-Adaptive Pareto Approach Beneficial for Controlling Embodied Virtual Robots?. The Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2003), Chicago, Lecture Notes in Computer Science LNCS2723, Springer-Verlag, 1612-1613, July.
  163. Abbass H.A. (2003). Pareto Neuro-Evolution: Constructing Ensemble of Neural Networks Using Multi-objective Optimization. The IEEE Congress on Evolutionary Computation (CEC2003), IEEE-Press, Vol. 3, pages 2074-2080, Australia.
  164. Abbass H.A., Bagirov A.M., and Zhang J. (2003). The Discrete Gradient Evolutionary Strategy Method for Global Optimization. The IEEE Congress on Evolutionary Computation (CEC2003), IEEE-Press, Vol. 1, pages 435-442, Australia.
  165. Teo J. and Abbass H.A. (2003). Elucidating the Benefits of a Self-Adaptive Pareto EMO Approach for Evolving Legged Locomotion in Artificial Creatures. The IEEE Congress on Evolutionary Computation (CEC2003), IEEE-Press, Vol. 2, pages 755-762, Australia.
  166. Shan Y., McKay R.I., Abbass H.A., and Essam D. (2003). Program Evolution with Explicit Learning. The IEEE Congress on Evolutionary Computation (CEC2003), IEEE-Press, Vol. 3, pages 1639-1646, Australia.
  167. Liu B., McKay R.I., and Abbass H.A. (2003). Improving Genetic Classifiers with a Boosting Algorithm. The IEEE Congress on Evolutionary Computation (CEC2003), IEEE-Press, Vol. 4, pages 2596-2602, Australia.
  168. Hoai N.X., McKay R.I., and Abbass H.A. (2003). Bias in Tree Adjoining Grammars. In Proceedings of the European Conference on Genetic Programming (EUROGP), Essex, Lecture Notes in Computer Science LNCS2610, Springer-Verlag, 335-344, January.
  169. Essam D. and Abbass H.A. (2003). Artificial Life Models for Security and Safety. The First Australian Conference on Artificial Life (ACAL2003), Canberra, ACT, Australia, pages 73-85, December 2003.
  170. Teo J. and Abbass H.A. (2003). Neuro-Morpho Evolution: What Will Happen If Our Body Is Not Symmetric?The First Australian Conference on Artificial Life (ACAL2003), Canberra, ACT, Australia, pages, 261-275, December 2003.
  171. Liu B., Abbass H.A., McKay B. (2003). Classification Rule Discovery with Ant Colony Optimization. The IEEE/WIC International Conference on Intelligent Agent Technology (IAT 2003), Halifax, Canada.
  172. Sarker R. and Abbass H.A. (2003). Identification of Future ADF Vehicles and Trailer Fleets for project Overlander. Proceedings of the 2002 Mathematics-in-Industry Study Group, UniSA, Adelaide, Australia, pp. 35-52.
  173. Abbass H.A. (2003). Pareto Neuro-Ensemble. The 16th Australian Joint Conference on Artificial Intelligence (AI03), Perth, Lecture Notes in Artificial Intelligence LNAI 2903, Springer-Verlag, 554-566.
  174. Teo J. and Abbass H.A. (2003). Software Verification of Redundancy in Neuro-Evolutionary Robotics. The 16th Australian Joint Conference on Artificial Intelligence (AI03), Lecture Notes in Artificial Intelligence LNAI 2903, Springer-Verlag, 302-314.
  175. Abbass H.A. and Deb K. (2003). Searching under multi-evolutionary pressures. In Proceedings of the 2003 Evolutionary Multiobjective Optimization Conference (EMO03), Faro, Lecture Notes in Computer Science LNCS2632, Springer-Verlag, 391-404.
  176. Wang B.B., McKay R I., Abbass H.A. and Barlow M. (2003). A Comparative Study for Domain Ontology Guided Feature Extraction. In Proceedings of the Australian Computer Society Conference, Australia.
  177. Abbass H.A. (2002). Self-adaptive Pareto Differential Evolution. The IEEE Congress on Evolutionary Computation (CEC2002).
  178. Abbass H.A., Hoai N.X., and McKay R.I. (2002). AntTAG: A new method to compose computer programs using colonies of ants. The IEEE Congress on Evolutionary Computation (CEC2002).
  179. Teo J. and Abbass H.A. (2002). Multi-objectivity for brain-behavior evolution of a physically-embodied organism. In Standish, R., Bedau, M., and Abbass, H., editors, Artificial Life VIII: The 8th International Conference on Artificial Life, pages 312-318, Cambridge, MA. MIT Press, 2002.
  180. Teo J. and Abbass H.A. (2002). Coordination and synchronization of locomotion in a virtual robot. In Wang, L., Rajapakse, J., Fukushima, K., Lee, S., and Yao, X., editors, Proceedings of the 9th International Conference on Neural Information Processing (ICONIP02), volume 4, pages 1931-1935, 2002.
  181. Teo J. and Abbass H.A. (2002). Trading-off mind complexity and locomotion in a physically simulated quadruped. In Wang, L., Tan, K., Furuhashi, T., Kim, J., and Yao, X., editors, Proceedings of the 4th Asia-Pacific Conference on Simulated Evolution And Learning (SEAL02), volume 2, pages 776-780, 2002.
  182. Barlow M., Galloway J., and Abbass H.A. (2002). Mining Evolution Through Visualization . Beyond Fitness: Visualising Evolution. a Workshop at the 8th International Conference on the Simulation and Synthesis of Living Systems (ALife 8), Sydney, Australia, December, 2002.
  183. Abbass H.A. (2001). Marriage in Honey Bees Optimisation: A Haplometrosis Polygynous Swarming Approach. The IEEE Congress on Evolutionary Computation (CEC2001), Seoul, Korea.
  184. Abbass H.A., Sarkar R., and Newton C. (2001). A pareto differential evolution approach to vector optimisation problems. The IEEE Congress on Evolutionary Computation (CEC2001), Seoul, Korea.
  185. Abbass H.A. (2001). A Single Queen Single Worker Honey Bees Approach to 3-SAT. The Genetic and Evolutionary Computation Conference, GECCO2001, San Francisco, USA, 2001.
  186. Abbass H.A. (2001). A Memetic Pareto Evolutionary Approach to Artificial Neural Networks. The Australian Joint Conference on Artificial Intelligence, Adelaide, Lecture Notes in Artificial Intelligence LNAI 2256, Springer-Verlag, 1-12, December.
  187. Macrossan P.E., Abbass H.A., Mengersen K., Towsey M. and Finn G. (1999). Bayesian neural network learning for prediction in the Australian dairy industry. Intelligent Data Analysis, Amsterdam, Lecture Notes in Computer Science LNCS1642, Springer-Verlag, 395-406, August.

Book Chapters

  1. Abbass, H. A. (2020). An Introduction to Neuroergonomics: From Brains at Work to Human-Swarm Teaming. In Neuroergonomics. Chang S. Nam (Eds), 3-10, Springer, Cham, ISBN 978-3-030-34783-3.
  2. Yaxley, K. J., Joiner, K. F., Bogais, J., and Abbass, H. A. (2020). Life Learning of Smart Autonomous Systems for Meaningful Human‐Autonomy Teaming. A Framework of Human Systems Engineering: Applications and Case Studies. Holly Handley and Andreas Tolk (Eds), 43-61, Wiley-IEEE Press, ISBN: 978-1-119-69875-3.
  3. Wang M., Abbass H.A., and Hu J. (2018). EEG-based Biometrics for Person Identification and Continuous Authentication, In Information Security: Foundations, technologies and applications. Awad A.I. and Fairhurst M. (Eds), Institution of Engineering and Technology (IET) publisher, 2018. ISBN 978-1-84919-974-2
  4. Wang, K., Petraki, E., and Abbass, H. (2016). Evolving Narrations of Strategic Defence and Security Scenarios for Computational Scenario Planning. In Recent Advances in Computational Intelligence in Defense and Security (pp. 635-661). Springer International Publishing.
  5. Bui L.T., Essam D., and Abbass H.A. (2010) The Role of Explicit Niching and Communication Messages in Distributed Evolutionary Multi-objective Optimization. In F. Fernández de Vega and E. Cantú-Paz (Eds.): Parallel and Distributed Computational Intelligence, SCI 269, pp. 181-206. Springer-Verlag Berlin, Heidelberg 2010.
  6. Zhao, W, Tang, J, Alam, S, Bender, A, Abbass H.A. (2010) Evolutionary-Computation Based Risk Assessment of Aircraft Landing Sequencing Algorithms, IFIP Advances in Information and Communication Technology, Vol 329/2010, 254-265, Springer.
  7. Bui L.T., Bender A., Barlow M., and Abbass H.A. (2010) Multiagent-Based Approach for Risk Analysis in Mission Capability Planning. In R. Sarker and R. Tapabrata (Eds): Agent-Based Evolutionary Search, Adaptation, Learning and Optimization Series, Vol 5, 77-96.
  8. Soliman O., Bui L.T., and Abbass H.A. (2009). A Memetic Coevolutionary Multi-Objective Differential Evolution Algorithm. In Multi-Objective Memetic Algorithms, C-K. Goh, Y-S. Ong, K.C. Tan (Eds). Springer, Studies in Computational Intelligence, Vol (171), Pages 369-388, ISBN 978-3-540-88050-9.
  9. Dam H.H., Rojanavasu P., Abbass H.A. and Lokan C. (2008). Distributed Learning Classifier Systems. In Learning Classifier Systems in Data Mining, Larry Bull and Ester Bernado-Mansilla and John H. Holmes (Eds), Springer, Studies in Computational Intelligence Series, Pages 69-91, Vol (125), ISBN 978-3-540-78978-9.
  10. Teo J., Neri L.D., Nguyen M.H. and Abbass H.A. (2008). Walking with EMO: Multi-Objective Robotics for Evolving Two, Four and Six Legged Locomotion. In Multi-Objective Optimization in Computational Intelligence: Theory and Practice, Lam Thu Bui and Sameer Alam (Eds), chapter 11, pages 300-332, IGI Global Publications.
  11. Bui L.T., Nguyen M.H., Branke J., Abbass H.A. (2008) Tackling Dynamic Problems with Multiobjective Evolutionary Algorithms. In Multiobjective Problem Solving from Nature: From Concepts to Applications, Joshua Knowles, David Corne, and Kalyanmoy Deb (Eds), Springer, Natural Computing Series, Pages 77-92, ISBN 978-3-540-72963-1.
  12. Dam H.H., Rojanavasu P., Abbass H.A. and Lokan C. (2007) Distributed learning classifier systems. In Learning Classifier Systems in Data Mining, Bull, L., Bernado Mansilla, E. & Holmes, J. (eds), Springer, In Press
  13. Bui L.T., Nguyen M.H., Branke J., and Abbass H.A., Tackling Dynamic Problems with Multiobjective Evolutionary Algorithms. In Multiobjective Problem Solving from Nature: From Concepts to Applications, Joshua Knowles, David Corne, and Kalyanmoy Deb (Eds), Springer, pp. 77-92, December 2007.
  14. Dam H.H., Lokan C. and Abbass H.A. (2007) Evolutionary Online Data Mining: An Investigation in a Dynamic Environment. In Evolutionary Computation in Dynamic and Uncertain Environments, Shengxiang Yang, Yew-Soon Ong and Yaochu Jin Edition, Studies in Computational Intelligence Series, Springer, Volume 51/2007, pages 153- 178, ISBN 978-3-540-49772-1
  15. Baker S., Bender A., Abbass H.A., and Sarker R. (2007) A Scenario-based Evolutionary Scheduling Approach for Assessing Future Supply Chain Fleet Capabilities, In Evolutionary Scheduling, K. Dahal, K.C. Tan and P. Cowling (eds.), Studies in Computational Intelligence Series, Springer, Volume 49/2007, pages 485-512, ISBN 978-3-540- 48582-7.
  16. Shan Y., McKay R.I., Essam D.L. and Abbass H.A. (2006) A Survey of Probabilistic Model Building Genetic Programming, In Scalable Optimization via Probabilistic Modeling, Series: Studies in Computational Intelligence, Vol. 33 Pelikan M., Sastry K., and Cantú-Paz E. (Eds), Springer-Verlag, 121-160.
  17. Abbass H.A. (2005) Pareto-Optimal Approaches to Neuro-Ensemble Learning, In Multi-Objective Machine Learning, Series: Studies in Computational Intelligence, Jin, Yaochu (Ed), Springer-Verlag, 407-428.
  18. Kirley M., Abbass H., and McKay R. (2006) "Diversity Mechanisms in Pitt-Style Evolutionary Classifier Systems", In Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques, E. Triantaphyllou and G. Felici, Springer-Verlag, New York, NY, U.S.A., in its Massive Computing series, Vol. 6. ISBN 0-3873-4294-X, 433- 458.
  19. Teo J. and Abbass H.A. (2004) Evolutionary Multi-objective Robotics: Evolving Physically Simulated Quadruped using the Pareto-frontier Differential Evolution Algorithm, In Recent Advances in Simulated Evolution and Learning, K.C. Tan, M.H. Lim, X. Yao and L. Wang (Eds), World Scientific, ISBN 981-238-952-0, pp.466-485.
  20. Nguyen M.H., Abbass H.A. and McKay R. (2004) Diversity and Neuro-Ensemble, In Evolutionary Computing in Data Mining, A. Ghosh and L. Jain, Physica-Verlag, Germany.
  21. Abbass H.A., Towsey M., Kozan E., Van Der Werf J., and Diederich J. "A Markov Chain Tabu Search Approach to the evolutionary allocation problem". In Operations Research/ Management Science at Work: Applying Theory in the Area Pacific Region, E. Kozan and A. Ohuchi Eds, Kluwer Academic Publishers. 

Editorship

  1. 2020-Now Founding Editor-in-Chief, IEEE Transactions on Artificial Intelligence, IEEE
  2. 2021-Now Associate Editor, IEEE Transactions on Emerging Topics in Computational Intelligence, IEEE
  3. 2020-Now Associate Editor, ACM Computing Surveys, ACM
  4. 2017-2019 Associate Editor, IEEE Transactions on Computational Social Systems, IEEE
  5. 2016-Now Associate Editor, IEEE Transactions on Cybernetics, IEEE
  6. 2016-Now Associate Editor, IEEE Transactions on Cognitive and Developmental Systems, IEEE
  7. 2015-Now Associate Editor, Cognitive Computation, Springer
  8. 2015-Now Associate Editor, Natural Computing, Springer
  9. 2015-Now Editor, Complex & Intelligent Systems, Springer
  10. 2013-2014 Editor, Applied Soft Computing, ElsevierÂ
  11. 2011-2014 Associate Editor, Journal of Industrial and Management Optimization, American Institute of Mathematical Sciences
  12. 2010-Now Associate Editor, IEEE Transactions on Evolutionary Computation, IEEE
  13. 2010-Now Associate Editor, International Journal of Artificial Life Research
  14. 2010-2016 Associate Editor, IEEE Computational Intelligence Magazine, IEEE
  15. 2007-Now Associate Editor, International Journal of Intelligent Computing and Cybernetics, Emerald
  16. 2006-2010 Editorial Board, International Journal of Applied Systemic Studies (IJASS), Inderscience

Invited Talks

  1. Invited Speaker: 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI 2020), 19-20 December 2020, Bangladesh. Title: Tenants of Trust and Transparency in Human-Swarm Teaming: Interpretability, Explainability, and Predictability.
  2. Invited Speaker: Conference on Artificial Intelligence and Data Analytics for Air Transportation, February 3 to February 4, 2020, Singapore. Title: Apprenticeship Bootstrapping: Intelligent Shepherds for Swarm Traffic Management Systems.
  3. Invited Speaker: 24th International Society of Air-breathing Engines, September 22 to September 27, 2019, Canberra, Australia. Title: Artificial Intelligence: How our UNSW-Canberra research is transforming the Air to breathe smartness.
  4. Invited Speaker: The rise of complex autonomous systems: current challenges for national security policymakers, Institute For Regional Security - Future Strategic Leaders Congress 18-20 May 2018.
  5. Invited Speaker: D61+DSTG Cyber Summer School, 12-13 February 2018, Title: Towards Milliseconds Autonomous Learning in Trusted Human-Swarm Cognitive-Cyber-Physical Missions.
  6. Invited Speaker: 1st International Workshop on Human Intelligent machIne cOexistane (HELIOS) , 9-10 January 2018, Singapore. Title: Trusted Autonomy in Closed Loop Human Machine Systems.
  7. Invited Speaker: Australasian Conference on Artificial Life and Computational Intelligence, January 31 to February 2, 2017, Geelong, Melbourne. Title: Trusted Autonomy: Challenges and Opportunities for Computational Intelligence.
  8. Invited Speaker: Innovation Month, July 21, 2015, Canberra. Title: Welcome Mr and Mrs RoboGov.
  9. Invited Speaker: Emerging Disruptive Technologies Assessment Symposium (EDTAS), July 15-17, 2015, Canberra. Title: Trust in Humans and Machines.
  10. Invited Speaker: Research Forum Semi-autonomous systems: trust, control, and letting go, November 10-11, 2015, Defence Science Institute, The Beauty and the Beast of Trusted Autonomy.
  11. Invited Speaker: Emerging Disruptive Technologies Assessment Symposium: Trusted Autonomy, July 15-17, 2015, Defence Science and Technology Group, On Trust in Humans and Machines .
  13. Invited Speaker: Australasian Conference on Artificial Life and Computational Intelligence, February 5-7, 2015, Newcastle. Title: Cognitive-Cyber Symbiosis.
  14. Invited Speaker: The Seventh IEEE Symposium on Computational Intelligence for Security and Defense Applications , December, 14-17, 2014, Hanoi Vietnam, Computational Red Teaming for Cognitive-Cyber Symbiosis.
  15. Invited Speaker: The 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems, November, 10-12, 2014, Singapore, Real-time Computational Red Traming of Human Cognition using Encephalographic (EEG) Data.
  16. Invited Speaker: The Fourth International Neural Network Society Symposia Series , November, 7-9, 2014, Brunei, Next Generation Intelligent Systems: Observe-Project-Counteract Agent Architecture for Real-time Computational Red Teaming.
  17. Invited Lecture: Evolutionary Multi-objective Optimisation for Scenario Design and Real-time Optimisation, National University of Singapore, April 2014.
  18. Invited Seminar: Institute for Infocomm Research (I²R), Agency for Science, Technology and Research (A*STAR), March 25, 2014, Singapore, Computational Red Teaming for Integrating the Air Traffic Controller Brain and the Automation Cycle.
  19. Invited Seminar: Rolls-Royce, March 14, 2014, Singapore, Computational Red Teaming for Future Automation Systems.
  20. Invited Visiting Professor: A Course on Computational Red Teaming, National Defence Academy of Japan, October 2013
  21. Invited Speaker: The 2013 IEEE Symposium on Computational Intelligence for Human-like Intelligence, IEEE SSCI 2013, April, 16-19, 2013, Singapore, Human Experiments in Computational Intelligence.
  22. Invited Speaker: The 47th Annual Conference on Statistics, Computer Sciences, and Operations Research, December, 24-27, 2012, Cairo University, Egypt, Role of Optimisation and Simulation in Intelligent Systems.
  23. Invited Speaker: The 9th International Conference on Simulated Evolution and Learning, SEAL 2012, December 2012, Ha Noi, Viet Nam, Computational Red Teaming: Can Evolution and Learning Augment Human Behaviour? .
  24. Invited Speaker: The 1st International Conference on Robot Intelligence Technology and Applications, RiTA 2012, December 2012, Gwangju, Seoul, South Korea, Computational Red Teaming for Air Traffic Management.
  25. Invited Speaker: International Workshop on Nature Inspired Computation and Applications, IWNICA'12, October 2012, Hefei, China, Talk 1: Neural learning using multi-objective estimation methods". Talk 2: "Automatic decomposition and the role of architecture in mining Big Data.
  26. Invited Speaker: Networked Enabled Operations, NEO2012, June 2012, Canberra, Australia, Dancing with uncertainty in networked capabilities: How to manoeuvre in human, cyber and physical terrains.
  27. Invited Speaker: Australian Data Mining Conference, ADM 2011, December 2011, Victoria, Australia, Mining Big Data Streams: The Fallacy of Blind Correlation and the Importance of Models.
  28. Invited Speaker: Network Centric Operations, NCO Asia 2011, September 2011, Singapore, Network Based Planning And Computational Red Teaming.
  29. Invited Speaker: Doctoral Intensive Summer School on meta-heuristics in optimization and intelligent data analysis, 21-26 June, 2011, Alexandru Ioan Cuza, Romania.
  30. Invited Speaker: The IEEE World Congress on Computational Intelligence, WCCI 2010, 18-23 July 2010, Barcelona, Spain, Evolutionary Computation for Risk Assessment and Management.
  31. Invited speaker: the International Civil Aviation Organization (ICAO), Reduced Vertical Separation Minimum Safety, Bahrain, Feb 2010
  32. Invited Speaker: Network Centric Warfare, NCW 2010, 28-30 April 2010, Canberra, Australia, Outlining The Risk Assessment Of Networked Environments.
  33. Invited Speaker: Platform Technologies Research Institute Annual Symposium, PTRI 09, 14-15 July, 2009, Computational Red Teaming and Cyber Challenges.
  34. Invited Speaker: The IEEE Symposium: Computational Intelligence for Security and Defence Applications, CISDA 2009, 8-10 July 2009, Ottawa, Canada, Forward, Reverse and Emerging Dynamics: Can Complex Adaptive Systems Play a Game with the Unknown? .
  35. Invited Speaker: The 14th International Symposium on Artificial Life and Robotics, AROB 2009, 5-7 February 2009, Beppu, Oita, Japan, The Role of Non-Dominance in Artificial Life and Robotics.
  36. Invited Speaker: The 7th International Conference on Simulated Evolution and Learning, SEAL 2008, 7-10 December 2008, Melbourne, Australia, The Future of Intelligent Systems is Non-Dominance.
  37. Invited Speaker: The 12th Asia Pacific Symposium on Intelligent and Evolutionary Systems, 7-8 December 2008, Melbourne, Australia, The Future of Intelligent Systems is Non-Dominance.
  38. Keynote: Operations Research in Australia: The Experts Speak, Canberra, Australia, 7-8 July, 2008, Structuring the strategic scenario planning process.
  39. Invited Speaker: 3rd International Nonlinear Science Conference, Chuo University, Tokyo, Japan, 13-15 March, 2008, Characterising and Understanding dynamics in reactive heterogeneous multi-agent systems.
  40. Invited Speaker at the Defence and Security track of Complex ’07, Gold Coast, Australia, Signatures of Game Dynamics for Intelligence and Information Operation.
  41. Invited Speaker at the International Seminar Series, Intelligent Robot Research Centre, Advanced Institute of Science and Technology (KAIST), Korea, November 2006. Recent Advances on Artificial Life and Adaptive Robotics.
  42. Invited Speaker at the 8th Asia Pacific Symposium on Intelligent and Evolutionary Systems, 6-7 Dec 2004, Cairns, Australia. The lone thinker of Celigny in learning and agent systems.
  43. Department of Veterans' Affairs, Australia, Data Mining, 21/10/2003.
  44. DPI, Australia, 20/09/1998. Introducing Neural Networks for the Dairy Industry, a talk was given in The Dept. of Primary Industries, Workshop for extensions, Sunshine Coast.

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