Hussein Abbass

Complete list

Research

Publications

Authored Books

4 records

Edited Volumes

21 records

Journal Manuscripts

151 records

Conference Papers

256 records

  • Wasswa, H., Abbass, H. and Lynar, T. (2026) ‘How the Graph Construction Technique Shapes Performance in IoT Botnet Detection: Insights from Graph Attention Networks’, in Computing and Pattern Recognition. pp. 524–535.

    Open publication

  • Eumi, E. M., Abbass, H. and Marcus, N. (2025) ‘SwarmChat: An LLM-Based, Context-Aware Multimodal Interaction System for Robotic Swarms’, in Advances in Swarm Intelligence. pp. 181–192.

    Open publication

  • Greenwood, G., Abbass, H. and Hussein, A. (2024) ‘Harmonizing Individual and Group Interests: A Strategy for Fostering Cooperation in Social Dilemma Games’. In 2024 International Conference on Emerging Techniques in Computational ….

  • Diggelen, J.V., Burken, C.B.V. and Abbass, H. (2024) ‘Team design patterns for meaningful human control in responsible military artificial intelligence’. In International conference on bridging the gap between AI and reality, 40-54.

  • Liu, J., Singh, H., Elsayed, S., Hunjet, R. and Abbass, H. (2023) ‘Distance constrained robotic swarm shepherding based on two-phase ant colony optimisation’. In 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC ….

  • Liu, J., Singh, H., Elsayed, S., Hunjet, R. and Abbass, H. (2023) ‘Effective robotic swarm shepherding in the presence of obstacles’. In 2023 IEEE Congress on Evolutionary Computation (CEC), 1-8.

  • Wasswa, H., Lynar, T. and Abbass, H. (2023) ‘Enhancing IoT-botnet detection using variational auto-encoder and cost-sensitive learning: A deep learning approach for imbalanced datasets’. In 2023 IEEE Region 10 Symposium (TENSYMP), 1-6.

  • Greenwood, G., Abbass, H. and Hussein, A. (2023) ‘Interpretation of neural network players for a generalized divide the dollar game using SHAP values’. In 2023 IEEE symposium series on computational intelligence (SSCI), 1808-1813.

  • Wasswa, H., Lynar, T., Nanyonga, A. and Abbass, H. (2023) ‘Iot botnet detection: Application of vision transformer to classification of network flow traffic’. In 2023 Global Conference on Information Technologies and Communications (GCITC ….

  • Nguyen, D., Singh, H., Elsayed, S., Hunjet, R. and Abbass, H. (2023) ‘Multi-agent Knowledge Transfer in a Society of Interpretable Neural Network Minds for Dynamic Context Formation in Swarm Shepherding’. In 2023 International Joint Conference on Neural Networks (IJCNN), 1-9.

  • Hussein, A., Petraki, E., Elsawah, S. and Abbass, H. (2022) ‘Autonomous swarm shepherding using curriculum-based reinforcement learning’. In Proceedings of the 21st International Conference on Autonomous Agents and ….

  • Dam, T., Ferdaus, M., Pratama, M., Anavatti, S., Jayavelu, S. and Abbass, H. (2022) ‘Latent preserving generative adversarial network for imbalance classification’. In 2022 IEEE International Conference on Image Processing (ICIP), 3712-3716.

  • Dong, X., Garratt, M., Anavatti, S., Abbass, H. and Dong, J. (2022) ‘Lightweight monocular depth estimation with an edge guided network’. In 2022 17th International Conference on Control, Automation, Robotics and ….

  • Baxter, D., Hepworth, A., Joiner, K. and Abbass, H. (2022) ‘On the premise of a swarm guidance ontology for human-swarm teaming’. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting 66 (1 ….

  • Mohamed, R., Elsayed, S., Hunjet, R. and Abbass, H. (2022) ‘Reinforcement learning for solving communication problems in shepherding’. In 2022 IEEE Symposium Series on Computational Intelligence (SSCI), 1626-1635.

  • Simpson, J., Oosthuizen, R., Sawah, S. and Abbass, H. (2021) Agile, antifragile, artificial-intelligence-enabled, command and control. International Conference on Command and Control. arXiv preprint arXiv:2109.06874.

  • Mohamed, R., Elsayed, S., Hunjet, R. and Abbass, H. (2021) ‘A graph-based approach for shepherding swarms with limited sensing range’. In 2021 IEEE congress on evolutionary computation (CEC), 2315-2322.

  • Debie, E., Singh, H., Elsayed, S., Perry, A., Hunjet, R. and Abbass, H. (2021) ‘A neuro-evolution approach to shepherding swarm guidance in the face of uncertainty’. In 2021 IEEE international conference on systems, man, and cybernetics (SMC ….

  • Mandziuk, J. and Abbass, H. (2021) ‘Conference Report on 2021 IEEE Congress on Evolutionary Computation (IEEE CEC 2021)[Conference Reports]’. In IEEE computational intelligence magazine 16 (4), 5-8.

  • Mańdziuk, J. and Abbass, H. (2021) ‘Conference Report on 2021 IEEE Congress on Evolutionary Computation (IEEE CEC 2021)[Conference Reports]’. In IEEE Computational Intelligence Magazine 16 (4), 5-8.

  • Campbell, B., El-Fiqi, H., Hunjet, R. and Abbass, H. (2021) ‘Distributed multi-agent shepherding with consensus’. In International Conference on Swarm Intelligence, 168-181.

  • Dam, T., Ferdaus, M., Anavatti, S., Jayavelu, S. and Abbass, H. (2021) ‘Does adversarial oversampling help us?’. In Proceedings of the 30th ACM International Conference on Information ….

  • Abbass, H., Anavatti, S., Senthilnath, J. and Ferdaus, M. (2021) ‘Does Adversarial Oversampling Help us?’. In Proceedings of the 30th ACM International Conference on Information ….

  • Buckley, A., Strydom, R., Niven, R. and Abbass, H. (2021) ‘On dependability in human-swarm teaming: Toward qualification of smart autonomous systems’. In AIAC 2021: 19th Australian International Aerospace Congress: 19th Australian ….

  • Francis, S., Anavatti, S., Garratt, M. and Abbass, H. (2021) ‘Real-time multi-obstacle detection and tracking using a vision sensor for autonomous vehicle’. In Communication and Intelligent Systems: Proceedings of ICCIS 2020, 873-883.

  • McCall, F., Hussein, A., Petraki, E., Elsawah, S. and Abbass, H. (2021) ‘Towards a systematic educational framework for human-machine teaming’. In 2021 IEEE international conference on engineering, technology & education ….

  • Liu, J., Hussein, A., Anavatti, S., Garratt, M. and Abbass, H. (2021) ‘UGV path planning based on an improved continuous ant colony optimisation algorithm’. In 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 01-08.

  • Mohamed, R., Hunjet, R., Elsayed, S. and Abbass, H. (2021) Deep learning for noisy communication system. 2021 31st International Telecommunication Networks and Applications.

  • El-Fiqi, H., Campbell, B., Elsayed, S., Perry, A., Singh, H., Hunjet, R., Abbass, H. and . (2020) ‘A preliminary study towards an improved shepherding model’. In Proceedings of the 2020 Genetic and Evolutionary Computation Conference ….

  • Nguyen, H., Garratt, M., Bui, L. and Abbass, H. (2020) ‘Disturbances in influence of a shepherding agent is more impactful than sensorial noise during swarm guidance’. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 2257-2264.

  • Elsayed, S., Singh, H., Debie, E., Perry, A., Campbell, B., Hunjel, R. and Abbass, H. (2020) ‘Path planning for shepherding a swarm in a cluttered environment using differential evolution’. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 2194-2201.

  • Nguyen, T., Liu, J., Nguyen, H., Kasmarik, K., Anavatti, S., Garratt, M. and Abbass, H. (2020) ‘Perceptron-learning for scalable and transparent dynamic formation in swarm-on-swarm shepherding’. In 2020 International Joint Conference on Neural Networks (IJCNN), 1-8.

  • Hussein, A., Elsawah, S. and Abbass, H. (2020) ‘Swarm collective wisdom: A fuzzy-based consensus approach for evaluating agents confidence in global states’. In 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8.

  • Vahidnia, S., Abbasi, A. and Abbass, H. (2020) A framework for understanding the dynamics of science: A case study on AI. Procedia Computer Science 177, 581-586.

  • Hussein, A., Elsawah, S. and Abbass, H. (2020) Towards Trust-Aware Human-Automation Interaction: An Overview of the Potential of Computational Trust Models. HICSS, 1-10.

  • Nguyen, H. T., Nguyen, T. D., Garratt, M., Kasmarik, K., Anavatti, S., Barlow, M. and Abbass, H. A. (2019) ‘A Deep Hierarchical Reinforcement Learner for Aerial Shepherding of Ground Swarms’, in Neural Information Processing. pp. 658–669.

    Open publication

  • Hussein, A., Elsawah, S. and Abbass, H. (2019) ‘A system dynamics model for human trust in automation under speed and accuracy requirements’. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63 (1 ….

  • Tang, J., Abbass, H. and Alam, S. (2019) ‘An airspace collision risk simulator for safety assessment’. In 2019 Winter Simulation Conference (WSC), 3160-3171.

  • Nguyen, H., Garratt, M., Bui, L. and Abbass, H. (2019) ‘Apprenticeship learning for continuous state spaces and actions in a swarm-guidance shepherding task’. In 2019 IEEE Symposium Series on Computational Intelligence (SSCI), 102-109.

  • Liu, J., Anavatti, S. and Abbass, M. (2019) ‘Comprehensive learning particle swarm optimisation with limited local search for UAV path planning’. In 2019 IEEE symposium series on computational intelligence (SSCI), 2287-2294.

  • Wade, H. and Abbass, H. (2019) ‘Cyber-shepherd: A smartphone-based game for human and autonomous swarm control’. In 2019 IEEE international conference on systems, man and cybernetics (SMC ….

  • Rojas, R.F., Debie, E., Fidock, J., Barlow, M., Kasmarik, K., Anavatti, S. and . (2019) ‘Encephalographic assessment of situation awareness in teleoperation of human-swarm teaming’. In International conference on neural information processing, 530-539.

  • El-Fiqi, H., Kasmarik, K., Bezerianos, A., Tan, K. and Abbass, H. (2019) ‘Gate-layer autoencoders with application to incomplete EEG signal recovery’. In 2019 International Joint Conference on Neural Networks (IJCNN), 1-8.

  • Hussein, A., Elsawah, S. and Abbass, H. (2019) ‘Investigating Gender Differences in Human Interactions with a Transparent Swarm’. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63 (1 ….

  • Abbass, H., Elsawah, S., Petraki, E. and Hunjet, R. (2019) ‘Machine Education: Designing semantically ordered and ontologically guided modular neural networks’. In 2019 IEEE Symposium Series on Computational Intelligence (SSCI), 948-955.

  • Clayton, N. and Abbass, H. (2019) ‘Machine teaching in hierarchical genetic reinforcement learning: Curriculum design of reward functions for swarm shepherding’. In 2019 IEEE congress on evolutionary computation (CEC), 1259-1266.

  • Singh, H., Campbell, B., Elsayed, S., Perry, A., Hunjet, R. and Abbass, H. (2019) ‘Modulation of force vectors for effective shepherding of a swarm: A bi-objective approach’. In 2019 IEEE congress on evolutionary computation (CEC), 2941-2948.

  • Greenwood, G., Abbass, H. and Petraki, E. (2019) ‘Punishing untrustworthiness and free riders to maintain cooperation in multi-agent social dilemmas using fuzzy logic’. In Proceedings of the 2019 11th International Conference on Computer and ….

  • Gee, A. and Abbass, H. (2019) ‘Transparent machine education of neural networks for swarm shepherding using curriculum design’. In 2019 International Joint Conference on Neural Networks (IJCNN), 1-8.

  • Chica, M., Chiong, R., Ramasco, J. and Abbass, H. (2019) Effects of update rules on networked N-player trust game dynamics. Communications in Nonlinear Science and Numerical Simulation 79, 104870.

  • Long, N., Sgarioto, D., Garratt, M., Sammut, K. and Abbass, H. (2019) Multi-vessel sea state estimation utilising swarm shepherding. RINA, Royal Institution of Naval Architects-Pacific 2019 International ….

  • Greenwood, G., Abbass, H. and Petraki, E. (2018) ‘A critical analysis of punishment in public goods games’. In 2018 IEEE Conference on Computational Intelligence and Games (CIG), 1-5.

  • Nguyen, H., Garratt, M. and Abbass, H. (2018) ‘Apprenticeship bootstrapping’. In 2018 International Joint Conference on Neural Networks (IJCNN), 1-8.

  • Nguyen, H., Garratt, M., Bui, L. and Abbass, H. (2018) ‘Apprenticeship Bootstrapping: Inverse Reinforcement Learning in a Multi-Skill UAV-UGV Coordination Task’. In Proceedings of the 17th International Conference on Autonomous Agents and ….

  • El-Fiqi, H., Wang, M., Salimi, N., Kasmarik, K., Barlow, M. and Abbass, H. (2018) ‘Convolution neural networks for person identification and verification using steady state visual evoked potential’. In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

  • Wang, M., Hussein, A., Rojas, R., Shafi, K. and Abbass, H. (2018) ‘EEG-based neural correlates of trust in human-autonomy interaction’. In 2018 IEEE Symposium Series on Computational Intelligence (SSCI), 350-357.

  • Hussein, A. and Abbass, H. (2018) ‘Mixed initiative systems for human-swarm interaction: Opportunities and challenges’. In 2018 2nd Annual Systems Modelling Conference (SMC), 1-8.

    Open publication

  • Wang, M., Hu, J. and Abbass, H. (2018) ‘Multi-scale weighted inherent fuzzy entropy for EEG biomarkers’. In 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8.

  • Ma-Wyatt, A., Fidock, J. and Abbass, H. (2018) ‘Quantifying and predicting human performance for effective human-autonomy teaming’. In International Conference on Science and Innovation for Land Power, Defence ….

  • Nguyen, T., Nguyen, H., Debie, E., Kasmarik, K., Garratt, M. and Abbass, H. (2018) ‘Swarm Q-learning with knowledge sharing within environments for formation control’. In 2018 International Joint Conference on Neural Networks (IJCNN), 1-8.

  • Sarker, R., Abbass, H., Dunstall, S., Kilby, P., Davis, R. and Young, L. (2017) ‘Data and Decision Sciences in Action: Proceedings of the Australian Society for Operations Research Conference 2016’. In Springer.

  • Yang, Z., Merrick, K. and Abbass, H. (2017) ‘Handling Multi-Task Learning with Deep Reinforcement Learning’. In International Joint Conference on Artificial Intelligence.

  • Yang, Z., Merrick, K., Abbass, H. and Jin, L. (2017) ‘Multi-task deep reinforcement learning for continuous action control.’. In IJCAI 17, 3301-3307.

    Open publication

  • Nguyen, H., Garratt, M., Bui, L. and Abbass, H. (2017) ‘Supervised deep actor network for imitation learning in a ground-air UAV-UGVs coordination task’. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8.

  • Hossain, M., Alam, S. and Abbass, H. (2017) A dynamic multi-commodity flow optimization algorithm for estimating airport network capacity. Air Traffic Management and Systems II: Selected Papers of the 4th ENRI.

  • Wang, M., Abbass, H. and Hu, J. (2016) ‘Continuous authentication using EEG and face images for trusted autonomous systems’. In 2016 14th Annual Conference on Privacy, Security and Trust (PST), 368-375.

  • Liu, X., Merrick, K. and Abbass, H. (2016) ‘Designing artificial agents to detect the motive profile of users in virtual worlds and games’. In 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8.

  • Wang, M., Abbass, H., Hu, J. and Merrick, K. (2016) ‘Detecting rare visual and auditory events from EEG using pairwise-comparison neural networks’. In International Conference on Brain Inspired Cognitive Systems, 90-101.

  • Dunk, I. and Abbass, H. (2016) ‘Emergence of order in leader-follower boids-inspired systems’. In 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8.

  • Greenwood, G., Abbass, H. and Petraki, E. (2016) ‘Emotion, Trustworthiness and Altruistic Punishment in a Tragedy of the Commons Social Dilemma’. In Australasian Conference on Artificial Life and Computational Intelligence, 12-24.

  • Abdelfattah, S., Merrick, K. and Abbass, H. (2016) ‘Eye movements as information markers in EEG data’. In 2016 IEEE symposium Series on Computational Intelligence (SSCI), 1-7.

  • Greenwood, G., Abbass, H. and Petraki, E. (2016) ‘Finite population trust game replicators’. In Australasian Conference on Artificial Life and Computational Intelligence ….

  • Zhang, B., Shafi, K. and Abbass, H. (2016) ‘Hybrid knowledge-based evolutionary many-objective optimization’. In 2016 IEEE Congress on Evolutionary Computation (CEC), 1007-1014.

  • Goh, S., Abbass, H., Tan, K., Al-Mamun, A., Guan, C. and Wang, C. (2016) ‘Multiway analysis of EEG artifacts based on block term decomposition’. In 2016 International Joint Conference on Neural Networks (IJCNN), 913-920.

  • Harvey, J., Merrick, K. and Abbass, H. (2016) ‘Quantifying swarming behaviour’. In International Conference in Swarm Intelligence, 119-130.

  • Tang, J., Petraki, E. and Abbass, H. (2016) ‘Shaping influence and influencing shaping: A computational red teaming trust-based swarm intelligence model’. In International Conference in Swarm Intelligence, 14-23.

  • Abdelfattah, S., Merrick, K. and Abbass, H. (2016) ‘Theta-beta ratios are prominent EEG features for visual tracking tasks’. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60 (1 ….

  • Leu, G. and Abbass, H. (2015) ‘Computational red teaming in a sudoku solving context: Neural network based skill representation and acquisition’. In Intelligent and Evolutionary Systems: The 19th Asia Pacific Symposium, IES ….

  • Wenjing, Z., Richard, C. and Abbass, H. (2015) ‘Dynamic capacity-demand balance in air transport systems using co-evolutionary computational red teaming’. In Proceeding of the 5th international air transport and operations symposium.

  • Goh, S., Tan, K., Al-Mamun, A. and Abbass, H. (2015) ‘Evolutionary big optimization (BigOpt) of signals’. In 2015 IEEE Congress on Evolutionary Computation (CEC), 3332-3339.

  • Goh, S., Tan, K., Al-Mamun, A. and Abbass, H. (2015) ‘Evolutionary big optimization (BigOpt) of signals. İn: 2015 IEEE Congress on Evolutionary Computation, CEC’. In IEEE.

  • Al-Ani, A., Naik, G. R. and Abbass, H. A. (2015) ‘A methodology for synthesizing interdependent multichannel EEG data with a comparison among three blind source separation techniques’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 154-161.

  • Wang, B., Merrick, K. E. and Abbass, H. A. (2015) ‘Autonomous hypothesis generation as an environment learning mechanism for agent design’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 210-225.

  • Petraki, E. and Abbass, H. A. (2015) ‘On trust and influence: A computational red teaming game theoretic perspective’, in Proceedings of the 2014 7th IEEE Symposium on Computational Intelligence for Security and Defense Applications, CISDA 2014.

    Open publication

  • Falcon, R., Abielmona, R., Billings, S., Plachkov, A. and Abbass, H. (2015) ‘Risk management with hard-soft data fusion in maritime domain awareness’, in Proceedings of the 2014 7th IEEE Symposium on Computational Intelligence for Security and Defense Applications, CISDA 2014.

  • Swiechowski, M., Merrick, K., Mandziuk, J. and Abbass, H. (2015) Human-machine cooperation in general game playing. ACHI 2015, 108.

  • Abbass, H., Mańdziuk, J., Merrick, K. and Świechowski, M. (2015) Human-Machine Cooperation in General Game Playing. the ACHI.

  • Swiechowski, M., Merrick, K., Mandziuk, J. and Abbass, H. (2015) Human-machine cooperation loop in game playing. Int. J. Adv. Intell. Syst 8 (3/4), 310-323.

  • Abbass, H., Tang, J., Amin, R., Ellejmi, M. and Kirby, S. (2014) ‘Augmented cognition using real-time EEG-based adaptive strategies for air traffic control’. In Proceedings of the human factors and ergonomics society annual meeting 58.

  • Goh, S. K., Abbass, H. A., Tan, K. C. and Al Mamun, A. (2014) ‘Artifact removal from EEG using a multi-objective independent component analysis model’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 570-577.

  • Abbass, H. A. (2014) ‘Calibrating independent component analysis with laplacian reference for real-time EEG artifact removal’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 68-75.

  • Ren, S., Tang, J., Barlow, M. and Abbass, H. A. (2014) ‘An interactive evolutionary computation framework controlled via EEG signals’, in IEEE International Conference on Fuzzy Systems. pp. 2402-2409.

  • Shafi, K. and Abbass, H. A. (2014) ‘Analysis of online signature based learning classifier systems for noisy environments: A feedback control theoretic approach’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 395-406.

  • Tang, J. and Abbass, H. A. (2014) ‘Behavioral learning of aircraft landing sequencing using a society of Probabilistic Finite state Machines’, in Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014. pp. 610-617.

  • Leu, G., Tang, J. and Abbass, H. (2014) ‘On the role of working memory in trading–off skills and situation awareness in sudoku’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 571-578.

  • Greenwood, G. W., Elsayed, S., Sarker, R. and Abbass, H. A. (2014) ‘Online generation of trajectories for autonomous vehicles using a multi-agent system’, in Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014. pp. 1218-1224.

  • Zhang, B., Shafi, K. and Abbass, H. (2014) ‘Online knowledge-based evolutionary multi-objective optimization’, in Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014. pp. 2222-2229.

  • Abbass, H. A., Mount, W. M., Tuček, D. and Pinheiro, J. P. (2014) ‘Towards a code of best practice for evaluating air traffic control interfaces’, in ATRF 2011 - 34th Australasian Transport Research Forum.

  • Amin, R., Tang, J., Ellejmi, M., Kirby, S. and Abbass, H. A. (2014) ‘Trading-off simulation fidelity and optimization accuracy in air-traffic experiments using differential evolution’, in Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014. pp. 475-482.

  • Hossain, M., Alam, S., Rees, T. and Abbass, H. (2013) ‘Australian airport network robustness analysis: A complex network approach’, in Australasian Transport Research Forum, ATRF 2013 - Proceedings.

  • Long, N., Bui, L. T. and Abbass, H. (2013) ‘A new niching method for the direction-based multi-objective evolutionary algorithm’, in Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, MCDM 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013. pp. 1-8.

  • 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’, in Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems, CIVTS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013. pp. 64-71.

  • Amin, R., Tang, J., Ellejmi, M., Kirby, S. and Abbass, H. A. (2013b) ‘Computational red teaming for correction of traffic events in real time human performance studies’, in Proceedings of the 10th USA/Europe Air Traffic Management Research and Development Seminar, ATM 2013.

  • Ghoneim, A., Greenwood, G. W. and Abbass, H. (2013) ‘Distributing cognitive resources in one-against-many strategy games’, in 2013 IEEE Congress on Evolutionary Computation, CEC 2013. pp. 1387-1394.

  • Wang, K., Bui, V., Petraki, E. and Abbass, H. A. (2013) ‘Evolving story narrative using surrogate models of human judgement’, in Advances in Intelligent Systems and Computing. pp. 653-661.

  • Wang, S. L., Shafi, K., Lokan, C. and Abbass, H. A. (2013) ‘Neuro-evolution of escape behaviour under high level of deception and noise’, in Advances in Intelligent Systems and Computing. pp. 671-681.

  • Alam, S., Hossain, M., Lokan, C., Barry, S., Aldis, G., Butcher, R. and Abbass, H. (2013) ‘Real time prediction of worst case air traffic sector collision risk using evolutionary optimization’, in Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems, CIVTS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013. pp. 72-79.

  • Zhang, B., Shafi, K. and Abbass, H. A. (2013) ‘Robo-teacher: A computational simulation based educational system to improve cyber security’, in Advances in Intelligent Systems and Computing. pp. 179-186.

  • Zhang, B., Shafi, K. and Abbass, H. A. (2012) ‘A density based approach to the access point layout smart distribution grid design optimization problem’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 73-82.

  • 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’, in 2012 IEEE Congress on Evolutionary Computation, CEC 2012.

  • Mount, W. M., Tuček, D. C. and Abbass, H. A. (2012) ‘A psychophysiological analysis of weak annoyances in human computer interfaces’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 202-209.

  • Bui, V., Bender, A. and Abbass, H. (2012) ‘An expressive GL-2 grammar for representing story-like scenarios’, in 2012 IEEE Congress on Evolutionary Computation, CEC 2012.

  • Vu, C. C., Bui, L. T. and Abbass, H. A. (2012) ‘DEAL: A direction-guided evolutionary algorithm’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 148-157.

  • Wang, B., Merrick, K. E. and Abbass, H. A. (2012) ‘Developing attention focus metrics for autonomous hypothesis generation in data mining’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 290-299.

  • Wang, K., Bui, V., Petraki, E. and Abbass, H. A. (2012) ‘From subjective to objective metrics for evolutionary story narration using event permutations’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 400-409.

  • Ren, S., Barlow, M. and Abbass, H. A. (2012) ‘Frontal cortex neural activities shift cognitive resources away from facial activities in real-time problem solving’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 132-139.

  • Shafi, K., Bender, A. and Abbass, H. A. (2012) ‘Multi objective learning classifier systems based hyperheuristics for modularised fleet mix problem’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 381-390.

  • Xiong, J., Shafi, K. and Abbass, H. A. (2012) ‘Multi-Uncertainty Problems (MUP) with applications to managing risk in resource-constrained project scheduling’, in 2012 IEEE Congress on Evolutionary Computation, CEC 2012.

  • Tuček, D. C., Mount, W. M. and Abbass, H. A. (2012) ‘Neural and speech indicators of cognitive load for Sudoku game interfaces’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 210-217.

  • Mount, W. M., Tuček, D. C. and Abbass, H. A. (2012) ‘Psychophysiological evaluation of task complexity and cognitive performance in a human computer interface experiment’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 600-607.

  • Alam, S., Lokan, C. and Abbass, H. (2012) ‘What can make an airspace unsafe? characterizing collision risk using multi-objective optimization’, in 2012 IEEE Congress on Evolutionary Computation, CEC 2012.

  • Leu, G., Curtis, N. and Abbass, H. (2012) ‘Modeling and evolving human behaviors and emotions in road traffic networks’. Procedia-Social and Behavioral Sciences 54, 999-1009.

  • El-Fiqi, H., Petraki, E. and Abbass, H. A. (2011) ‘A computational linguistic approach for the identification of translator stylometry using Arabic-English text’, in IEEE International Conference on Fuzzy Systems. pp. 2039-2045.

  • Bui, L. T., Baker, S., Bender, A., Abbass, H. A., Barlow, M. and Saker, R. (2011) ‘A grid-based heuristic for two-dimensional packing problems’, in 2011 IEEE Congress of Evolutionary Computation, CEC 2011. pp. 2329-2336.

  • Xiong, J., Chen, Y., Liu, J. and Abbass, H. A. (2011) ‘An evolutionary multi-objective scenario-based approach for Stochastic Resource Investment Project Scheduling’, in 2011 IEEE Congress of Evolutionary Computation, CEC 2011. pp. 2767-2774.

  • Ghoneim, A. S., Essam, D. L. and Abbass, H. A. (2011) ‘Competency awareness in strategic decision making’, in 2011 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support, CogSIMA 2011. pp. 106-109.

  • Alam, S., Zhao, W., Tang, J., Lokan, C., Abbass, H., Ellejmi, M. and Kirby, S. (2011) ‘Discovering delay patterns in arrival traffic with dynamic continuous descent approaches using co-evolutionary red teaming’, in Proceedings of the 9th USA/Europe Air Traffic Management Research and Development Seminar, ATM 2011. pp. 174-183.

  • Shafi, K., Bender, A. and Abbass, H. A. (2011) ‘Fleet estimation for defence logistics using a multi-objective Learning Classifier System’, in Genetic and Evolutionary Computation Conference, GECCO'11. pp. 1195-1202.

  • Abbass, H. (2011) ‘Mining big data streams: the fallacy of blind correlation and the importance of models’. In Proceedings of the Ninth Australasian Data Mining Conference-Volume 121, 5-6.

  • Alam, S., Nguyen, M. H., Abbass, H. A., Lokan, C., Ellejmi, M. and Eurocontrol, S. K. (2010) ‘A dynamic continuous descent approach methodology for low noise and emission’, in AIAA/IEEE Digital Avionics Systems Conference - Proceedings.

  • 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’, in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010.

  • Bui, V., Abbbass, H. and Bender, A. (2010) ‘Evolving stories: Grammar evolution for automatic plot generation’. In Ieee congress on evolutionary computation, 1-8.

  • Pham, V. V., Bui, L. T., Alam, S., Lokan, C. and Abbass, H. A. (2010) ‘A Pittsburgh Multi-Objective Classifier for user preferred trajectories and flight navigation’, in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010.

  • Hossain, M. M., Abbass, H. A., Lokan, C. and Alam, S. (2010) ‘Adversarial Evolution: Phase transition in non-uniform hard satisfiability problems’, in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010.

  • Shafi, K., Bender, A. and Abbass, H. A. (2010) ‘Evolutionary dynamics of interdependent exogenous risks’, in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010.

  • Wang, K., Bui, V. Q. and Abbass, H. A. (2010) ‘Evolving stories: Tree adjoining grammar guided genetic programming for complex plot generation’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 135-145.

  • Purton, L., Abbass, H. and Alam, S. (2010) ‘Identification of ADS-B system vulnerabilities and threats’, in ATRF 2010: 33rd Australasian Transport Research Forum.

  • Boulden, S., Iorio, A. W. and Abbass, H. A. (2010) ‘Learning synchronization in networked complex systems using genetic algorithms’, in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010.

  • Leu, G., Abbass, H. and Curtis, N. (2010) ‘Resilience of ground transportation networks: A case study on Melbourne’, in ATRF 2010: 33rd Australasian Transport Research Forum.

  • Wang, S. L., Shafi, K., Lokan, C. and Abbass, H. A. (2010) ‘Robustness of neural ensembles against targeted and random Adversarial Learning’, in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010.

  • Liu, J., Zhong, W., Abbass, H. A. and Green, D. G. (2010) ‘Separated and overlapping community detection in complex networks using multiobjective Evolutionary Algorithms’, in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010.

  • Abbass, H., Bender, A. and Whitbread, P. (2010) ‘Computational red teaming: Unravelling the pharaoh’s curse’. In Computational Intelligence in Security and Defence Applications Workshop.

  • Bui, L. T., Wesolkowski, S., Bender, A., Abbass, H. A. and Barlow, M. (2009) ‘A dominance-based stability measure for multi-objective evolutionary algorithms’, in 2009 IEEE Congress on Evolutionary Computation, CEC 2009. pp. 749-756.

  • Chen, K. Y., Lindsay, P. A., Robinson, P. J. and Abbass, H. A. (2009) ‘A hierarchical conflict resolution method for multi-agent path planning’, in 2009 IEEE Congress on Evolutionary Computation, CEC 2009. pp. 1169-1176.

  • Alam, S., Abbass, H. A., Lokan, C. J., Ellejmi, M. and Kirby, S. (2009) ‘Computational red teaming to investigate failure patterns in Medium Term Conflict Detection’, in 8th Innovative Research Workshop and Exhibition, Proceedings. pp. 183-194.

  • Tang, J., Alam, S., Abbass, H. and Lokan, C. (2009) ‘Modelling and evolutionary multi-objective evaluation of interdependencies and work processes in airport operations’, in 2009 World Summit on Genetic and Evolutionary Computation, 2009 GEC Summit - Proceedings of the 1st ACM/SIGEVO Summit on Genetic and Evolutionary Computation, GEC'09. pp. 977-980.

  • Bui, V., Bui, L., Abbass, H., Bender, A. and Ray, P. (2009) ‘On the role of information networks in logistics: An evolutionary approach with military scenarios’, in 2009 IEEE Congress on Evolutionary Computation, CEC 2009. pp. 598-605.

  • 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’, in 2009 IEEE Congress on Evolutionary Computation, CEC 2009. pp. 2180-2187.

  • Abbass, H. A. (2009) ‘The Pareto operating curve for risk minimization in life and robotics’, in Proceedings of the 14th International Symposium on Artificial Life and Robotics, AROB 14th'09. pp. 1-4.

  • Abbass, H. (2009) ‘Computational red teaming and cyber challenges’. In Platform Technologies Research Institute Annual Symposium, PTRI 9, 14-15.

  • Abbass, H. A., Bender, A., Dam, H. H., Baker, S., Whitacre, J. and Sarker, R. (2008) ‘Computational scenario-based capability planning’, in GECCO'08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008. pp. 1437-1444.

  • Barbosa, B., Bui, L., Abbass, H., Aguirre, L. and Braga, A. (2008) ‘Evolving an Ensemble of Neural Networks Using Artificial Immune Systems’, in SIMULATED EVOLUTION AND LEARNING, PROCEEDINGS. p. 658.

  • Bui, L., Whitacre, J. and Abbass, H. (2008) ‘Performance Analysis of Elitism in Multi-objective Ant Colony Optimization Algorithms’, in 2008 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-8. p. 4207.

  • Whitacre, J. M., Abbass, H. A., Sarker, R., Bender, A. and Baker, S. (2008) ‘Strategic positioning in tactical scenario planning’, in GECCO'08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008. pp. 1081-1088.

  • Abbass, H., Bender, A., Baker, S. and Sarker, R. (2007) ‘Anticipating future scenarios for the design of modularised vehicle and trailer fleets’. In SimTecT2007, Simulation Conference.

  • Bui, L., Soliman, O. and Abbass, H. (2007) ‘A modified strategy for the constriction factor in particle swarm optimization’, in PROGRESS IN ARTIFICIAL LIFE, PROCEEDINGS. p. 402.

  • Bui, L., Nguyen, M., Branke, J. and Abbass, H. (2007) Tackling dynamic problems with multiobjective evolutionary algorithms. Multiobjective Problem Solving from Nature: From Concepts to Applications, 77-91.

  • Greenwood, G. and Abbass, H. (2007) ‘A new local search algorithm for continuous spaces based on army ant swarm raids’, in IEEE Congress on Evolutionary Computation. pp. 1097-1102.

  • Barlow, M., Yang, A. and Abbass, H. (2007) ‘A temporal risk assessment framework for planning a future force structure’, in IEEE Symposium on Computational Intelligence in Security and Defense Applications. p. 219.

  • Alam, S., Nguyen, M., Abbass, H. and Barlow, M. (2007) ‘Ants guide future pilots’, in PROGRESS IN ARTIFICIAL LIFE, PROCEEDINGS. p. 402.

  • Chen, K. Y., Dam, H. H., Lindsay, P. A. and Abbass, H. A. (2007) ‘Biasing XCS with domain knowledge for planning flight trajectories in a moving sector free flight environment’, in Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007. pp. 456-462.

  • Yang, A., Abbass, H. and Sarker, R. (2007) ‘Group coordination in multi-agent systems: Is it a necessity or an overhead?’, in MODSIM07 - Land, Water and Environmental Management: Integrated Systems for Sustainability, Proceedings. pp. 670-676.

  • Ursani, Z., Sarker, R. and Abbass, H. (2007) ‘Improving the performance of genetic algorithm in capacitated vehicle routing problem using self imposed constraints’, in IEEE Symposium on Computational Intelligence in Scheduling. p. 285.

  • Ghoneim, A., Abbass, H. and Barlow, M. (2007) ‘Information sharing in the Iterated Prisoner's Dilemma game’, in IEEE Symposium on Computational Intelligence and Games. pp. 56-62.

  • Ghoneim, A., Abbass, H. and Barlow, M. (2007) ‘Investigating alliance dynamics using a co-evolutionary iterated prisoner's dilemma with an exit option’, in IEEE Congress on Evolutionary Computation. pp. 4065-4072.

  • Shafi, K., Abbass, H. and Zhu, W. (2007) ‘Real time signature extraction from a supervised classifier system’, in 2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS. pp. 2509-2516.

  • Ghoneim, A., Barlow, M. and Abbass, H. (2007) ‘Rounds effect in evolutionary games’, in PROGRESS IN ARTIFICIAL LIFE, PROCEEDINGS. p. 402.

  • Ghoneim, A., Abbass, H. and Barlow, M. (2007) ‘The critical point when prisoners meet the minority: Local and global dynamics in mixed evolutionary games’, in IEEE Congress on Evolutionary Computation. pp. 3711-3718.

  • Soliman, O., Bui, L. and Abbass, H. (2007) ‘The effect of a stochastic step length on the performance of the differential evolution algorithm’, in 2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS. p. 4780.

  • Abbass, H. A., Bedau, M., Nolfi, S. and Wiles, J. (2007) ‘The first IEEE symposium on artificial life IEEE-ALife'07 april 1-5, 2007, Honolulu, Hawaii, USA’, in Proceedings of the 2007 IEEE Symposium on Artificial Life, CI-ALife 2007.

  • Abbass, H., Baker, S., Bender, A. and Sarker, R. (2007) Anticipating future army supply chain fleet capabilities. SimTecT.

  • Sarker, R., Kara, S., Freeman, G., Kayis, B., Ray, T. and Abbass, H. (2006) ‘A multi-agent simulation study for supply chain operation’, in International Conference on Computational Intelligence for Modelling, Control and Automation/International Conference on Intelligent Agents Web Technologies and International Commerce. pp. 728-733.

  • Chen, K., Dam, H., Lindsay, P. and Abbass, H. (2006) ‘Biasing XCS with domain knowledge for planning flight trajectories in a moving sector free flight environment’, in 2007 IEEE SYMPOSIUM ON ARTIFICIAL LIFE. p. 475.

  • Abbass, H., Barlow, M., Essam, D. and Yang, Y. (2006) ‘Connecting the dots to disconnect them - A study into network evolution and dynamics for analyzing terrorist networks - art. no. 60390M’, in Complex Systems. p. M390.

  • Bui, L., Deb, K., Abbass, H. and Essam, D. (2006) ‘Dual guidance in evolutionary multi-objective optimization by localization’, in SIMULATED EVOLUTION AND LEARNING, PROCEEDINGS. pp. 384-391.

  • Yang, A., Abbass, H. and Sarker, R. (2006) ‘Land combat scenario planning: A multiobjective approach’, in SIMULATED EVOLUTION AND LEARNING, PROCEEDINGS. pp. 837-844.

  • Alam, S., Abbass, H., Barlow, M. and Lindsay, P. (2006) ‘Mapping lessons from ants to free flight - An ant-based weather avoidance algorithm in free flight airspace - art. no. 60390N’, in Complex Systems. p. 298.

  • Alam, S., Abbass, H. A., Barlow, M. and Lindsay, P. (2006) ‘Mapping lessons from ants to Free Flight an ant-based weather avoidance algorithm in Free Flight airspace’, in Proceedings of SPIE - The International Society for Optical Engineering.

  • Goh, C., Quek, H., Tan, K. and Abbass, H. (2006) ‘Modeling civil violence: An evolutionary multi-agent, game theoretic approach’, in 2006 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-6. pp. 1609-1616.

  • Alam, S., Bui, L., Abbass, H. and Barlow, M. (2006) ‘Pareto meta-heuristics for generating safe flight trajectories under weather hazards’, in SIMULATED EVOLUTION AND LEARNING, PROCEEDINGS. pp. 829-836.

  • Yang, A., Abbass, H. A. and Sarker, R. (2006) ‘Risk assessment of capability requirements using WISDOM-II’, in Proceedings of SPIE - The International Society for Optical Engineering, art. no. 60390A.

  • Yang, A., Curtis, N., Abbass, H., Sarker, R. and Barlow, M. (2006) WISDOM-II: A Network Centric Model for Warfare. Complex Science for a Complex World, 149.

  • Shafi, K., Abbass, H. and Zhu, W. (2006) ‘The role of early stopping and population size in XCS for intrusion detection’, in SIMULATED EVOLUTION AND LEARNING, PROCEEDINGS. pp. 50-57.

  • Shafi, K., Abbass, H. and Zhu, W. (2006) ‘An adaptive rule-based intrusion detection architecture’. In Proceedings of the 2006 RNSA security technology conference. Canberra.

  • Abbass, H., Baker, S., Bender, A. and Sarker, R. (2006) ‘Identifying the fleet mix in a military setting’. In The second international intelligent logistics systems conference, 22-23.

  • Alam, S., Bui, L., Abbass, H. and Barlow, M. (2006) ‘Real-World Applications of Evolutionary Computation Techniques-Pareto Meta-heuristics for Generating Safe Flight Trajectories Under Weather Hazards’. In Lecture Notes in Computer Science 4247, 829-836.

  • Bui, L., Branke, J. and Abbass, H. (2005) ‘Multiobjective optimization for dynamic environments’, in 2005 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-3, PROCEEDINGS. p. 2871.

  • Bui, L., Abbass, H. and Essam, D. (2005) ‘Fitness inheritance for noisy evolutionary multi-objective optimization’, in Genetic and Evolutionary Computation Conference. p. 2244.

  • Bui, L., Branke, J. and Abbass, H. (2005) ‘Diversity as a selection pressure in dynamic environments’, in Genetic and Evolutionary Computation Conference. pp. 1557-1558.

  • Dam, H. H., Abbass, H. A. and Lokan, C. (2005) ‘DXCS: An XCS system for distributed data mining’, in GECCO 2005 - Genetic and Evolutionary Computation Conference. pp. 1883-1890.

  • Dam, H., Abbass, H. and Lokan, C. (2005) ‘Be real! XCS with continuous-valued inputs’. In Proceedings of the 7th annual workshop on Genetic and evolutionary.

  • Dam, H., Shafi, K. and Abbass, H. (2005) ‘Can evolutionary computation handle large datasets? A study into network intrusion detection’, in AI 2005: ADVANCES IN ARTIFICIAL INTELLIGENCE. pp. 1092-1095.

  • Dam, H., Abbass, H. and Lokan, C. (2005) ‘The performance of the DXCS system on continuous-valued inputs in stationary and dynamic environments’, in 2005 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-3, PROCEEDINGS. p. 2871.

  • Dam, H., Abbass, H. and Lokan, C. (2005) ‘Investigation on DXCS: An XCS system for distribution data mining, with continuous-valued inputs in static and dynamic environments’. In Proceedings of the IEEE Cogress on Evolutionary Computation.

  • Sastry, K., Abbass, H., Goldberg, D. and Johnson, D. (2005) ‘Sub-structural niching in estimation of distribution algorithms’, in Genetic and Evolutionary Computation Conference. p. 2244.

  • Sarker, R., Kara, S., Freeman, G., Kayis, B., Ray, T. and Abbass, H. (2005) ‘A multi-agent simulation study for supply chain operation’, in Proceedings - International Conference on Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 and International Conference on Intelligent Agents, Web Technologies and Internet. pp. 728-733.

  • Mcpartland, M., Nolfi, S. and Abbass, H. (2005) ‘Emergence of communication in competitive multi-agent systems: A Pareto multi-objective approach’, in Genetic and Evolutionary Computation Conference. p. 2244.

  • Yang, A., Abbass, H. and Sarker, R. (2005) ‘WISDOM-II: A network centric model for warfare’, in KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 3, PROCEEDINGS. pp. 813-819.

  • Yang, A., Abbass, H. and Sarker, R. (2005) ‘Evolving agents for network centric warfare’. In Proceedings of the 7th annual workshop on Genetic and evolutionary ….

  • Bui, L., Shan, Y., Qi, F. and Abbass, H. (2005) ‘Comparing two versions of differential evolution in real parameter optimization’. In The 2005 IEEE congress on evolutionary computation, CEC.

  • Abbass, H. and Yang, A. (2005) ‘Evolving agents for network centric warfare’. In Proceedings of the 7th annual workshop on Genetic and evolutionary computation.

  • Abbass, H. A. (2004) ‘An inexpensive cognitive approach for bi-objective optimization using bliss points and interaction’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 712-721.

  • Shan, Y., Mckay, R., Baxter, R., Abbass, H., Essam, D. and Nguyen, H. (2004) ‘Grammar model-based program evolution’, in Congress on Evolutionary Computation (CEC 2004). pp. 478-485.

  • Yang, A., Abbass, H. and Sarker, R. (2004) ‘Landscape dynamics in multi-agent simulation combat systems’, in AI 2004: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS. pp. 39-50.

  • Sastry, K., Abbass, H. A. and Goldberg, D. (2004) ‘Sub-structural niching in non-stationary environments’, in Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). pp. 873-885.

  • Hoai, N. X., Bob, R. I., McKay, D. E. and Abbass, H. A. (2004) ‘Toward an Alternative Comparison between Different Genetic Programming Systems’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 67-77.

  • Watson, J., Abbass, H., Lokan, C. and Lindsay, P. (2004) ‘Software engineering for artificial life, complex systems, and agent-based distillation’. In Proceedings of the 7th Asia-Pacific Conference on Complex Systems Cairns ….

  • Liu, B., Abbass, H. and Mckay, B. (2003) ‘Classification rule discovery with ant colony optimization’, in IEEE/WIC International Conference on Intelligent Agent Technology (IAT 2003). pp. 83-88.

  • Abbass, H. (2003) ‘Pareto neuro-evolution: Constructing ensemble of neural networks using multi-objective optimization’, in CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS. p. 2850.

  • Abbass, H. and Deb, K. (2003) ‘Searching under multi-evolutionary pressures’, in EVOLUTIONARY MULTI-CRITERION OPTIMIZATION, PROCEEDINGS. pp. 391-404.

  • Wang, B., Mckay, R., Abbass, H. and Barlow, M. (2003) ‘A comparative study for domain ontology guided feature extraction’. In ACSC 3, 69-78.

  • Hoai, N., Mckay, R. and Abbass, H. (2003) ‘Tree adjoining grammars, language bias, and genetic programming’, in GENETIC PROGRAMMING, PROCEEDINGS. pp. 335-344.

  • Shan, Y., Mckay, R., Abbass, H. and Essam, D. (2003) ‘Program evolution with explicit learning’, in CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS. p. 2850.

  • Abbass, H. (2003) ‘Pareto neuro-ensembles’, in AI 2003: ADVANCES IN ARTIFICIAL INTELLIGENCE. pp. 554-566.

  • Liu, B., Mckay, B. and Abbass, H. (2003) ‘Improving genetic classifiers with a boosting algorithm’, in CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS. pp. 2596-2602.

  • Abbass, H., Bagirov, A. and Zhang, J. (2003) ‘The discrete gradient evolutionary strategy method for global optimization’, in CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS. pp. 435-442.

  • Teo, J. and Abbass, H. (2003) ‘Multi-objectivity for brain-behavior evolution of a physically-embodied organism’. In Artificial Life VIII: The 8th International Conference on Artificial Life.

  • Teo, J. and Abbass, H. A. (2003) ‘Elucidating the benefits of a self-adaptive Pareto EMO approach for evolving legged locomotion in artificial creatures’, in 2003 Congress on Evolutionary Computation, CEC 2003 - Proceedings. pp. 755-762.

  • Teo, J. and Abbass, H. (2003) ‘Neuro-Morpho Evolution: What will happen if our body is not symmetric?’. In Australian Conference on Artificial Life, 261-275.

  • Teo, J. and Abbass, H. (2003) ‘Is a self-adaptive Pareto approach beneficial for controlling embodied virtual robots?’, in GENETIC AND EVOLUTIONARY COMPUTATION - GECCO 2003, PT II, PROCEEDINGS. pp. 1612-1613.

  • Teo, J., Nguyen, M. and Abbass, H. (2003) ‘Multi-objectivity as a tool for constructing hierarchical complexity’, in GENETIC AND EVOLUTIONARY COMPUTATION - GECCO 2003, PT I, PROCEEDINGS. pp. 483-494.

  • Teo, J. and Abbass, H. (2003) ‘Software verification of redundancy in neuro-evolutionary robotics’, in AI 2003: ADVANCES IN ARTIFICIAL INTELLIGENCE. pp. 302-314.

  • Teo, J. and Abbass, H. A. (2003) ‘Software verification of redundancy in neuro-evolutionary robotics’, in Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). pp. 302-314.

  • Hoai, N., McKay, R. and Abbass, H. (2003) ‘Bias in tree adjoining grammars’. In Proceedings of the European Conference on Genetic Programming (EUROGP).

  • Sarker, R., Abbass, H. and Newton, C. (2003) Solving two multi-objective optimization problems using evolutionary algorithm. Computational intelligence in control, 218-233.

  • Abbass, H. (2002) ‘The self-adaptive Pareto Differential Evolution algorithm’, in CEC'02: PROCEEDINGS OF THE 2002 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2. p. 2034.

  • Liu, B., Abbass, H. and McKay, B. (2002) ‘Density-based heuristic for rule discovery with ant-miner’. In The 6th Australia-Japan joint workshop on Intelligent and Evolutionary Systems.

  • Abbass, H., Hoai, X. and Mckay, R. (2002) ‘AntTAG: A new method to compose computer programs using colonies of ants’, in CEC'02: PROCEEDINGS OF THE 2002 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2. p. 2034.

  • Wang, B., Mckay, R., Abbass, H. and Barlow, M. (2002) ‘Learning text classifier using the domain concept hierarchy’, in International Conference on Communications, Circuits and Systems. pp. 1230-1234.

  • Barlow, M., Galloway, J. and Abbass, H. (2002) ‘Mining evolution through visualization’. In ALife VIII workshops, 103-112.

    Open publication

  • Shan, Y., Abbass, H., McKay, R. and Essam, D. (2002) ‘AntTAG: a further study’. In Proceedings of the Sixth Australia-Japan Joint Workshop on Intelligent and Evolutionary Systems.

  • Teo, J. and Abbass, H. (2002) ‘Trading-off mind complexity and locomotion in a physically simulated quadruped’. In Proceedings of the 4th Asia-Pacific conference on simulated evolution and ….

  • Teo, J. and Abbass, H. (2002) ‘Coordination and synchronization of locomotion in a virtual robot’, in 9th International Conference on Neural Information Processing. pp. 1931-1935.

  • Abbass, H., Towsey, M., Kozan, E. and Werf, J.V.D. (2002) A Markov Chain Tabu Search Approach to the Evolutionary Allocation Problem. Operations Research/Management Science at Work, 71-91.

  • Abbass, H., Sarker, R. and Newton, C. (2001) ‘PDE: A Pareto-frontier differential evolution approach for multi-objective optimization problems’, in PROCEEDINGS OF THE 2001 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2. p. 1441.

  • Abbass, H. (2001) ‘MBO: Marriage in honey bees optimization a haplometrosis polygynous swarming approach’, in PROCEEDINGS OF THE 2001 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2. p. 1441.

  • Abbass, H. A. (2001) ‘A memetic pareto evolutionary approach to artificial neural networks’, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). pp. 1-12.

  • Abbass, H. (2001) ‘A monogenous MBO approach to satisfiability’. In Proceeding of the international conference on computational intelligence for ….

  • Abbass, H. (2001) ‘A single queen single worker honey–bees approach to 3-SAT’. In Proceedings of the 3rd annual conference on genetic and evolutionary ….

  • Abbass, H. (2001) ‘A monogenous MBO approach to satisfiability, in The International Conference on Computational Intelligence for Modelling’. In Control and Automation, CIMCA.

  • Sarker, R., Abbass, H. and Karim, S. (2001) ‘An evolutionary algorithm for constrained multiobjective optimization problems’. In The 5th Australasia-Japan Joint Workshop. University of Otago, Dunedin, New Zealand.

  • McKay, R. and Abbass, H. (2001) ‘Analyzing anticorrelation in ensemble learning’. In Proceedings of 2001 conference on Artificial Neural Networks and Expert Systems.

  • Abbass, H. and Sarker, R. (2001) ‘Simultaneous evolution of architectures and connection weights in ANNs’. In Proceedings of Artificial Neural Networks and Expert System Conference, 16-21.

  • McKay, R. and Abbass, H. (2001) ‘Anticorrelation measures in genetic programming’. In Australasia-Japan Workshop on Intelligent and Evolutionary Systems, 45-51.

  • Darbyshire, P., Abbass, H., Barlow, M. and McKay, R. (2000) ‘A prototype design for studying emergent battlefield behaviour through multi-agent simulation’. In Proceedings of the Japan-Australia Workshop on Intelligent and Evolutionary Systems, 71-78.

  • Macrossan, P., Abbass, H., Mengersen, K., Towsey, M. and Finn, G. (1999) ‘Bayesian neural network learning for prediction in the Australian dairy industry’, in ADVANCES IN INTELLIGENT DATA ANALYSIS, PROCEEDINGS. pp. 395-406.

  • Abbass H.A., Bligh W., Towsey M, Finn G, and Tierney M. (1999) ‘Knowledge discovery in a dairy cattle database: (Automated knowledge acquisition) ’, in Proceedings of the Fifth International Conference of The International Society for Decision Support Systems (ISDS'99), Melbourne, Australia, July.

  • Abbass H.A., Wiggen G., Lakshmanan R. and Morton B. (1999) ‘Constraint Programming for Process Synthesis’, in The first international conference on the Practical Application of Constraint Technologies and Logic Programming (PACLP99), London, UK, April.

  • Abbass, H., Finn, G. and Towsey, M. (1999) ‘A meta-representation for integrating OR and AI in an intelligent decision support paradigm’. In Proceedings of the 15th National Conference of The Australian Society for ….

  • Abbass, H., Wiggins, G., Lakshmanan, R. and Morton, B. (1999) ‘Integrating optimisation and search: An Intelligent Tool for Chemical Process Synthesis’. In Proceedings of Practical Applications of Logic Programming.

  • Abbass, H., Bligh, W., Towsey, M., Tierney, M. and Finn, G. (1999) Knowledge discovery in a dairy cattle database: Automated knowledge acquisition. Proc. 1999 Meeting of the International Society for Decision Support Systems 15.

  • Abbass H.A., Towsey M. And Finn G. (1998) ‘An intelligent decision support system for dairy cattle mate-allocation’, in The Australian workshop for intelligent decision support and knowledge management (AWIDS'98), Sydney, Australia.

  • Abbass, H., Towsey, M. and Finn, G. (1998) ‘OR and data mining for intelligent decision support in the Australian dairy industry's breeding program’. In Proceedings of New Research in OR, ASOR, Brisbane, 1-23.

  • Abbass, H., Bahgat, R. and Rasmy, M. (1997) ‘From constraint logic programming (CLP) to decision making logic programming (DMLP)’. In First European Conference on Intelligent Management Systems in Operations, Salford University, UK.

  • Abbass H.A., Bahgat R.M.R., and Rasmy M.H. (1996) ‘The front-end of an intelligent goal programming system’, in 6th. International conference on computer theory and applications, Alex., Egypt, Sept..

  • Abbass H.A., Bahgat R.M.R., and Rasmy M.H. (1995) ‘Evaluation of constraint logic programming from an operations research point of view’, in The 3rd International conference on artificial intelligence, American University in Cairo, Egypt.

Book Chapters

25 records

  • Liu, J., Anavatti, S., Garratt, M. and Abbass, H. (2021) Marriage in Honey Bees Optimization in Continuous Domains. Handbook of AI-based Metaheuristics, 43-72.

  • Yaxley, K., Joiner, K., Bogais, J. and Abbass, H. (2020) Life Learning of Smart Autonomous Systems for Meaningful Human‐Autonomy Teaming. A Framework of Human Systems Engineering: Applications and Case Studies, 43-61.

  • Abbass, H. (2020) ‘An introduction to neuroergonomics: From brains at work to human-swarm teaming’. Neuroergonomics: Principles and Practice, 3-10. [2026 JIF (2025 JCR): 2.8]

  • Abielmona, R., Falcon, R., Zincir-Heywood, N. and Abbass, H. (2016) ‘Recent advances in computational intelligence in defense and security’, in Studies in Computational Intelligence. pp. 1-9.

  • Wang, K., Petraki, E. and Abbass, H. (2015) ‘Evolving narrations of strategic defence and security scenarios for computational scenario planning’, in Studies in Computational Intelligence. pp. 635-661.

    Open publication

  • Zhao, W., Tang, J., Alam, S., Bender, A. and Abbass, H. A. (2010) ‘Evolutionary-computation based risk assessment of aircraft landing sequencing algorithms’, in IFIP Advances in Information and Communication Technology. pp. 254-265.

  • 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 Studies in Computational Intelligence. pp. 181-206.

  • Soliman, O., Bui, L. T. and Abbass, H. (2009) ‘A memetic coevolutionary multi-objective differential evolution algorithm’, in Studies in Computational Intelligence. pp. 369-388.

  • Dam, H. H., Rojanavasu, P., Abbass, H. A. and Lokan, C. (2008) ‘Distributed learning classifier systems’, in Studies in Computational Intelligence. pp. 69-91.

  • 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. pp. 300-332.

  • Baker, S., Bender, A., Abbass, H. and Sarker, R. (2007) ‘A scenario-based evolutionary scheduling approach for assessing future supply chain fleet capabilities’, in Studies in Computational Intelligence. pp. 485-511.

  • Shan, Y., McKay, R. I., Essam, D. and Abbass, H. A. (2007) ‘A survey of probabilistic model building genetic programming’, in Studies in Computational Intelligence. pp. 121-160.

  • Dam, H. H., Lokan, C. and Abbass, H. A. (2007) ‘Evolutionary online data mining: An investigation in a dynamic environment’, in Studies in Computational Intelligence. pp. 153-178.

  • Cornforth, D., Abbass, H. and Larkin, H. (2007) Intelligent Evacuation Models for Fire and Chemical Hazard. Recent advances in security technology, 145.

  • Kirley, M., Abbass, H., Mckay, R., Triantaphyllou, E. and Felici, G. (2006) ‘Diversity mechanisms in Pitt-style evolutionary classifier systems’, in DATA MINING AND KNOWLEDGE DISCOVERY APPROACHES BASED ON RULE INDUCTION TECHNIQUES. pp. 433-457.

  • Abbass, H. and Jin, Y. (2006) ‘Pareto-optimal approaches to neuro-ensemble learning’, in MULTI-OBJECTIVE MACHINE LEARNING. pp. 407-427.

  • Sarker, R. A. and Abbass, H. A. (2006) ‘Simultaneous evolution of network architectures and connection weights in artificial neural networks’, in Artificial Neural Networks in Finance and Manufacturing. pp. 28-41.

  • Essam, D. and Abbass, H. A. (2005) ‘All hazards analysis: A complexity perspective’, in Applications of Information Systems to Homeland Security and Defense. pp. 1-16.

  • Alam, S., McPartland, M., Barlow, M., Lindsay, P. and Abbass, H. (2005) ‘Neural Evolution for Collision Detection & Resolution in a 2D Free Flight Environment’. Recent Advances In Artificial Life, Ch. 2, 13-28. [2026 JIF (2025 JCR): 1.5]

  • Bui, L., Abbass, H. and Essam, D. (2005) ‘Cooperative Coevolution of Genotype—Phenotype Mappings to Solve Epistatic Optimization Problems’. Recent Advances In Artificial Life, Ch. 3, 29-42. [2026 JIF (2025 JCR): 1.5]

  • Yang, A., Abbass, H., Barlow, M., Sarker, R. and Curtis, N. (2005) ‘Evolving Capability Requirements in WISDOM-II’. Recent Advances In Artificial Life, Ch. 25, 335-347. [2026 JIF (2025 JCR): 1.5]

  • Nguyen, M., Abbass, H., Mckay, R., Ghosh, A. and Jain, L. (2005) ‘Diversity and neuro-ensemble’, in EVOLUTIONARY COMPUTATION IN DATA MINING. pp. 125-156.

  • Yang, A., Abbass, H. A. and Sarker, R. (2005) ‘How hard is it to red team?’, in Applications of Information Systems to Homeland Security and Defense. pp. 46-78.

  • Teo, J. and Abbass, H. (2004c) ‘Evolutionary multi-objective robotics: evolving a physically simulated quadruped using the PDE algorithm’, in RECENT ADVANCES IN SIMULATED EVOLUTION AND LEARNING. p. 820.

  • Abbass, H., Sarker, R. and Newton, C. (2002) ‘From evolution to immune to swarm to.. ? A simple introduction to modern heuristics’, in DATA MINING: A HEURISTIC APPROACH. pp. 2-21.

Others

49 records

  • Abbass, H. A. (2026) Ethics Assurance in Swarm Engineering: Moral Vectoring Design Pattern for Decentralised Artificial Intelligence.

    Open publication

  • Wasswa, H., Abbass, H. and Lynar, T. (2026) How the Graph Construction Technique Shapes Performance in IoT Botnet Detection. arXiv preprint arXiv:2603.06654.

  • Hepworth, A., Assaad, Z., Wyatt, A. and Abbass, H. (2026) Meaningful Human Command: Towards a New Model for Military Human-Robot Interaction. arXiv preprint arXiv:2604.06611.

  • Wasswa, H., Abbass, H. and Lynar, T. (2025) A Quantized VAE-MLP Botnet Detection Model: A Systematic Evaluation of Quantization-Aware Training and Post-Training Quantization Strategies. arXiv preprint arXiv:2511.03201.

  • Wasswa, H., Abbass, H. and Lynar, T. (2025) Are GNNs worth the effort for IoT botnet detection? A comparative study of VAE-GNN vs. ViT-MLP and VAE-MLP approaches. arXiv preprint arXiv:2505.17363.

  • Wasswa, H., Abbass, H. and Lynar, T. (2025) Graph attention neural network for botnet detection: Evaluating autoencoder, vae and pca-based dimension reduction. arXiv preprint arXiv:2505.17357.

  • Akay, T., Tolley, H. and Abbass, H. (2025) Information-Theoretic Aggregation of Ethical Attributes in Simulated-Command. arXiv preprint arXiv:2507.12862.

  • Abbass, H., Akay, T. and Tolley, H. (2025) Information-Theoretic Aggregation of Ethical Attributes in Simulated-Command. arXiv e-prints, arXiv: 2507.12862.

  • Baxter, D., Hussein, A. and Abbass, H. (2024) ‘Interpretability of Swarm State Tensors using Neural Machine Translation’. TechRxiv 2024 (0806).

  • Liu, J., Singh, H., Elsayed, S., Hunjet, R. and Abbass, H. (2023) Planning-assisted autonomous swarm shepherding with collision avoidance. arXiv preprint.

  • Nguyen, D., Kasmarik, K. and Abbass, H. (2022) Fusing interpretable knowledge of neural network learning agents for swarm-guidance. arXiv preprint arXiv:2204.00272.

  • Dam, T., Anavatti, S. and Abbass, H. (2021) Improving clustergan using self-augmented information maximization of disentangling latent spaces. arXiv preprint arXiv:2107.12706.

  • Dam, T., Swami, N., Anavatti, S. and Abbass, H. (2021) Multi-fake evolutionary generative adversarial networks for imbalance hyperspectral image classification. arXiv preprint arXiv:2111.04019.

  • 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.

    Open publication

  • Nguyen, T., Kasmarik, K. and Abbass, H. (2020) An exact transformation from deep neural networks to multi-class multivariate decision trees. arXiv preprint arXiv:2003.04675.

  • Nguyen, H., Nguyen, T., Tran, V., Garratt, M., Kasmarik, K., Anavatti, S. and . (2020) Continuous deep hierarchical reinforcement learning for ground-air swarm shepherding. arXiv preprint arXiv:2004.11543.

  • Nguyen, T., Kasmarik, K. and Abbass, H. (2020) Q-Learning with Differential Entropy of Q-Tables. arXiv preprint arXiv:2006.14795.

  • Nguyen, D., Kasmarik, K. and Abbass, H. (2020) Towards interpretable ANNs: An exact transformation to multi-class multivariate decision trees. arXiv preprint arXiv:2003.04675.

  • Nguyen, H., Tran, V., Nguyen, T., Garratt, M., Kasmarik, K., Barlow, M., Anavatti, S. and . (2018) Apprenticeship bootstrapping via deep learning with a safety net for UAV-UGV interaction. arXiv preprint arXiv:1810.04344.

  • Abbass, H., Harvey, J. and Yaxley, K. (2018) Lifelong testing of smart autonomous systems by shepherding a swarm of watchdog artificial intelligence agents. arXiv preprint arXiv:1812.08960.

  • Hussein, A., Ghignone, L., Nguyen, T., Salimi, N., Nguyen, H., Wang, M. and . (2018) Towards bi-directional communication in human-swarm teaming: A survey. arXiv preprint arXiv:1803.03093.

  • Abbass, H. (2017) An AI professor explains: three concerns about granting citizenship to robot Sophia. The conversation.

  • Iorio, A., Abbass, H., Gaidow, S. and Bender, A. (2014) Visualizing cognitive moves for assessing information perception biases in decision making. arXiv preprint arXiv:1401.7193.

  • Abbass, H., Bender, A. and Gaidow, S. (2010) Evolutionary computation for risk assessment using computational red teaming. Proc. IEEE World Congr. Computational Intelligence, Plenary and Invited Lectures.

  • Whitacre, J., Bender, A., Baker, S., Fan, Q., Sarker, R. and Abbass, H. (2009) Network topology and time criticality effects in the modularised fleet mix problem. arXiv preprint arXiv:0907.0597.

  • Wesolkowski, S., Mazurek, M., Whitacre, J., Bender, A. and Abbass, H. (2009) Robustness and Adaptiveness Analysis of Future Fleets. arXiv preprint arXiv:0907.0598.

  • Alam, S., Tang, J., Lokan, C. and Abbass, H. (2009) An assessment of BADA fuel flow methodologies for in-trail procedure evaluation. Defence & Security Applications Research Centre, University of New South ….

  • Yang, A., Curtis, N., Abbass, H. and Sarker, R. (2008) NCMAA: A network centric multi-agent architecture for modelling complex adaptive systems. The Artificial Life and Adaptive Robotics Laboratory Technical Report Series.

  • Alam, S., Shafi, K., Abbass, H. and Barlow, M. (2007) ‘Evolving air traffic scenarios for the evaluation of conflict detection models’. In Proc. 6th Eurocontrol Innovative Research Workshop, Eurocontrol Experiment Centre, Brétigny, France.

  • Nguyen, M., Alam, S., Tang, J. and Abbass, H. (2007) ‘Ants-inspired dynamic weather avoidance trajectories in a traffic constrained enroute airspace’ In Proc. 6th Eurocontrol Innovative Research Workshop, Eurocontrol Experiment Centre, Brétigny, France.

  • Nguyen, M., Alam, S., Tang, J. and Abbass, H. (2007) ‘Dynamic weather avoidance trajectories in a traffic constrained en route airspace’. In Proc. 6th Eurocontrol Innovative Research Workshop, Eurocontrol Experiment Centre, Brétigny, France.

  • Vallis, R., Yang, Y. and Abbass, H. (2006) Disciplinary approaches to terrorism: A survey. ALAR–The Artificial Life and Adaptive Robotics Laboratory: Technical Reports.

  • Alam, S., Abbass, H., Barlow, M. and Lindsay, P. (2006) Multi-objective ant colony optimization for weather avoidance in a free flight environment. The Artificial Life and Adaptive Robotics Laboratory, University of New South Wales.

  • Sawah, S., Abbass, H. and Sarker, R. (2006) Risk in interdependent systems: a framework for analysis and mitigation through orchestrated adaptation. Technical Report TR-ALAR-200611013, University of New South Wales.

  • Dam, H., Abbass, H. and Lokan, C. (2006) ‘BCS: a Bayesian learning classifier system’. Tech. Rep. TR-ALAR-200604005, The Artificial Life and Adaptic Robotics …. [2026 JIF (2025 JCR): 1.5]

  • Yang, A., Abbass, H. and Sarker, R. (2005) A comparison study of WISDOM and MANA in a networked environment. Technical Report TR-ALAR-200512001, University of New South Wales, ADFA ….

  • Yang, A., Abbass, H., Sarker, R. and Barlow, M. (2005) Network centric multi-agent systems: A novel architecture. Artificial Life and Adaptive Robotics Laboratory, ALAR Technical Report.

  • Abbass, H., Sastry, K. and Goldberg, D. (2005) Oiling the Wheels of Change: The Role of Adaptive Automatic Problem Decomposition in Non--Stationary Environments. arXiv preprint cs/0502021.

  • Abbass, H., Sastry, K. and Goldberg, D. (2004) Oiling the wheels of change: The role of adaptive automatic problem decomposition in non-stationary environments (IlliGAL Report No. 2004029). Urbana, IL: University of Illinois at Urbana-Champaign, Illinois Genetic ….

  • Abbass, H., Bacardit, J., Butz, M. and Llora, X. (2004) Online adaptation in learning classifier systems: stream data mining. Illinois Genetic Algorithms Laboratory, University of Illinois at Urbana ….

  • Sastry, K., Abbass, H. and Goldberg, D. (2004) Sub-structural niching in non-stationary environments (IlliGAL Report No. 2004035). Urbana, IL: Illinois Genetic Algorithms Laboratory, University of Illinois ….

  • Teo, J. and Abbass, H. (2001) An annealing approach to the mating-flight trajectories in the marriage in honey bees optimization algorithm Technical Report CS04/01. Academic Press, School of Computer Science, University of New South Wales at ….

  • Abbass, H., Towsey, M. and Finn, G. (1998) ‘An intelligent decision support system for dairy cattle mate-allocation’. In Proceedings of the third Australian workshop on intelligent decision support ….

  • Abbass H.A. (1998) ‘A quadratic optimiser in a constraint logic programming paradigm’. The workshop of constraint, 11th Australia Joint Conference in Artificial Intelligence, Australia, 1998.

  • Abbass, Alam and Pham (12/2008) TOP-LAT: Trajectory Optimisation and Prediction of Live Air Traffic.

  • Abbass, Alam and Tang (12/2008) RTA-COPACS: A Real Time Airspace COmplexity Prediction And Computation System.

  • Abbass and Alam (12/2008) UOSAD: A User Oriented Structuring of Airspace Data using a Novel Hierarchical Representation.

  • Abbass and Shafi (12/2008) TASET: Real-Time and Adaptive Signature Extraction and Classification SysTem.

  • Abbass, Alam, Barlow, Tang, Shafi, Nguyen and Truong (6/2008) Air Traffic Operations & Management Simulator (ATOMS).

Grants

  • 2020-2024 ($580,000), Abbass, Elsawah, and Petraki. Machine education for trusted multi-skilled evolutionary learners, DP200101211, ARC Discovery

  • 2016-2020 ($560,000), Abbass, Merrick, Tan (PI - Int. Investigator), Bezerianos (PI - Int. Investigator) User-task co- adaptation for effective interactive simulation environments, DP160102037, ARC Discovery

  • 2014-2016 ($399,000) Abbass, Challenging systems to discover vulnerabilities using computational red teaming, DP140102590, ARC Discovery

  • 2011-2013 ($315,000 (ARC) + $120,000 (Air Services Australia)), Abbass, Lokan, Aldis, Dunstone, and Butcher, New real-time risk indicators to improve the efficiency, environmental impact and safety of air traffic management, LP110100488, ARC Linkage

  • 2011 ($500,000) Radom, Cairns, Crawford, Shen, Wade, Wilkins, Abbass, Dzurak, Evans, Wen, Poulton, Arnold, Botten, Ford, Rahmani, O'Neill, Cheung, Johnson, Henskens, Borwein, Marchant, Hagenbuchner, Tieu, Rose, Gillies, Harrison, Waters, Leedham, Murison, “Flexible architecture high-performance computing facility for the intersect consortium of New South Wales”, LE110100143, ARC LIEF

  • 2009-2011 ($360,000), Green and Abbass, Dual Phase Evolution in Networks, DP0987832, ARC Discovery

  • 2009 ($500,000), Poulton, Botten, Ford, Rahmani, Armfield, Kuyucak, Lewis, McPhedran, Muller, Radom, Abbass, Ball, Bursill, England, Khanna, Leonardi, Pitman, Wilkins, Esselle, Ranganathan, Steel, Henskens, EI von Nagy-Felsobuki, Marchant, “A high performance computing cluster and storage for the INTERSECT Consortium of NSW”, LE0989506, ARC LIEF

  • 2006-2008 ($306,000), Barlow and Abbass, Defence and Security Risk Assessment using Agent Based Distillations, DP0667123, ARC Discovery

  • 2005 ($15,000), Abbass and Yao (International) - Ensembles of Collaborative Neural Networks. LX0561255, ARC Linkage International

  • 2004-2008 ($1,950,000), Mendis, Lai, Dawson, Abbass, Ahmad, Batten, Bennetts, Bradford, Brooks, Burman, Caelli, Duffield, Fraser, Fragomeni, Garratt, Green, Grzebieta, Halgamuge, Hao, Horadam, Hutchinson, Jamalipour, Kotagiri, Kubik, Lambert, Lindsay, Lu, Mareels, Melchers, Miley, Mojarrabi, Pan, Pieprzyk, Petersen, Rubinov, Safavi-Naini, Schneider, Seberry, Singh, Sridharan, Stewart, Taylor, Van Deventer, Varadharajan, Warren, Weber, Williams, Wilson, Xie, Zhao, “Research Network for a Secure Australia (RNSA)”, RN0459557, ARC Networks

  • 2004-2008 ($1,500,000), Dewar, Abbass, Aste, Ball, Batchelor, Batten, Bernhardt, Bossomaier, Bradbury, Cairns, Chong, Denier, Farquhar, Finnigan, Frederiksen, Freeman, Gottwald, Grebogi, Green, Griffiths, Guttmann, Hamer, Hegland, Henry, Heyde, Liley, Lindsay, MacKay, Little, Metcalfe, Milne, Morriss, Owczarek, Pattison, Prokopenko, Quispel, Raupach, Roberts, Robinson, Robson, Shats, Sloan, Soria, Standish, Vincent, Vladimirov, Walker, Wiles, Williams, and Wilson, “Complex Open Systems Network (COSNet)”, RN0460006, ARC Networks

  • 2004-2006 ($513,934 (ARC) + $150,000 (NCR)), Jarrat, Bossomaier, and Abbass, Scenario Driven Management in a Network Environment, LP0453657, ARC Linkage

  • 2003-2008 ($5,250,000), Lindsay, Abbass, Abramson, Adams, Burrage, Dromey, Foster, Green, Hayes, Kaplan, McLachlan, Pailthorpe, Quiggin, and Sanderson, The ARC Centre for Complex Systems (ACCS), CE0348249, ARC Centre of Excellence

  • 2003-2004 ($20,000), Lai, Abbass, Arnold, Bergin, Bradley, Brooks, Fraser, Green, Hall, Harch, Heslehurst, Hutchison, Lambert, Lawrence, Lennard, Lindsay, Miley “Network for Australian security technologies integration”, ARC Seed Funding for Networks