Top of page
Global Site Navigation

School of Science

Local Section Navigation
You are here: Main Content

Associate Professor Philip Hingston

Associate Professor

Contact Information Telephone: +61 8 6304 6427, Email:, Campus: Joondalup, Room: JO18.313
Staff Member Details
Telephone: +61 8 6304 6427
Campus: Joondalup  
Room: JO18.313  


Philip is an Associate Professor within the School of Science.


  • PG Dip in Computer Studies, The University of Melbourne.
  • Bachelor of Science, The University of Western Australia.
  • Doctor of Philosophy (Mathematics), Monash University, 1979.


Recent Research Grants

  • Game based learning and educational data mining,  Edith Cowan University,  ECU Industry Collaboration Grant - 2014 (Round 1),  2014 - 2015,  $209,936.
  • Promoting Youth Mental Health Using Gaming Technology: An RCT Pilot Study,  Healthway (WA Health Promotion Foundation),  Healthway - Research Starter Grant,  2010 - 2012,  $29,072.
  • AE2 Simulation National Archives of Australia,  National Archives of Australia,  Grant - Ian Maclean Award,  2009 - 2011,  $21,000.
  • Versatile Care @ Residential Environment - V-C@RE(tm),  Nortel Networks,  Grant - Development,  2009 - 2010,  $49,374.
  • Literature and Computational Tool Review for Red Teaming,  Defence Science and Technology Group of the Department of Defence,  Grant,  2009 - 2010,  $10,000.
  • Evolutionary Design for Ore Processing Plants,  Australian Research Council,  Grant - Linkage (Projects),  2003 - 2005,  $232,994.

Recent Publications (within the last five years)

Book Chapters

  • Cowling, PI., Buro, M., Bida, M., Botea, A., Bouzy, B., Butz, MV., Hingston, P., Nau, D., Munoz-Avila, H., Sipper, M., (2013), Search in Real-Time Video Games. Artificial and Computational Intelligence in Games, 6(8), 1-19, Germany, DOI: 10.4230/DFU.Vol6.12191.i.
  • Bates Congdon, C., Hingston, P., Kendall, G., (2013), Artificial and Computational Intelligence for Games on Mobile Platforms. Artificial and Computational Intelligence in Games, 6(8), 101-108, Dagstuhl, Germany, DOI: 10.4230/DFU.Vol6.12191.101.

Journal Articles

  • Pech, A., Masek, M., Lam, P., Hingston, P., (2016), Game level layout generation using evolved cellular automata. Connection Science, 28(1), 63-82, DOI: 10.1080/09540091.2015.1130020.
  • Rastegari, S., Hingston, P., Lam, P., (2015), Evolving statistical rulesets for network intrusion detection. Applied Soft Computing Journal, 33(1 September 2015), 348-359, DOI: 10.1016/j.asoc.2015.04.041.
  • Ashlock, D., Brown, JA., Hingston, P., (2015), Multiple opponent optimization of prisoner's dilemma playing agents. IEEE Transactions on Computational Intelligence and AI in Games, 7(1), Article number 6819427, DOI: 10.1109/TCIAIG.2014.2326012.
  • Li, J., Hingston, P., Kendall, G., (2011), Engineering design of strategies for winning iterated prisoner's dilemma competitions. IEEE Transactions on Computational Intelligence and AI in Games, 3(4), 348-360, DOI: 10.1109/TCIAIG.2011.2166268.

Conference Publications

  • Wheat, D., Masek, M., Lam, P., Hingston, P., (2016), Modeling perceived difficulty in game levels. Proceedings of the Australasian Computer Science Week Multiconference, Article no. a74, New York, USA, DOI: 10.1145/2843043.2843478.
  • Pech, A., Lam, P., Hingston, P., Masek, M., (2016), Using isovists to evolve terrains with gameplay elements. Applications of Evolutionary Computation, 9597(30 Mar - 1 Apr 2016), 636-652, DOI: 10.1007/978-3-319-31204-0_41.
  • Adi, E., Baig, Z., Lam, P., Hingston, P., (2015), Low-rate denial-of-service attacks against HTTP/2 services. 2015 5th International Conference on IT Convergence and Security (ICITCS): Proceedings, Article num 7292994, DOI: 10.1109/ICITCS.2015.7292994.
  • Wheat, D., Masek, M., Lam, P., Hingston, P., (2015), Dynamic Difficulty Adjustment in 2D Platformers through Agent-Based Procedural Level Generation. Proceedings of the 2015 IEEE International Conference on Systems, Man and Cybernetics (SMC 2015), 2778-2785, Piscataway, N.J., DOI: 10.1109/SMC.2015.485.
  • Ashlock, D., Hingston, P., McGuinness, C., (2015), Evolving point packings in the plane. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8955(5-7 Feb 2015), 297-309, DOI: 10.1007/978-3-319-14803-8.
  • Rastegari, S., Lam, P., Hingston, P., (2015), A statistical rule learning approach to network intrusion detection. 2015 5th International Conference on IT Convergence and Security (ICITCS): Proceedings, Article no. 7292933, DOI: 10.1109/ICITCS.2015.7292933.
  • Pech, A., Hingston, P., Masek, M., Lam, P., (2015), Evolving Cellular Automata for Maze Generation. Artificial Life and Computational Intelligence: First Australasian Conference, ACALCI 2015, LNAI 8955(5-7 February 2015), 112-124, DOI: 10.1007/978-3-319-14803-8_9.
  • Ashlock, D., Hingston, P., (2014), Tego - A framework for adversarial planning. Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014, 13-20, Piscataway, N. J., DOI: 10.1109/CEC.2014.6900498.
  • While, L., Hingston, P., (2013), Usefulness of infeasible solutions in evolutionary search: An empirical and mathematical study. 2013 IEEE Congress on Evolutionary Computation (CEC), 1363-1370, Piscataway, N.J., DOI: 10.1109/CEC.2013.6557723.
  • Hingston, P., Congdon, CB., Kendall, G., (2013), Mobile Games with Intelligence: a Killer Application?. 2013 IEEE Conference on Computational Intelligence in Games(CIG), 1-7, Piscataway N. J., DOI: 10.1109/CIG.2013.6633660.
  • Rastegari, S., Hingston, P., Lam, P., Brand, M., (2013), Testing a Distributed Denial of Service Defence Mechanism using Red Teaming. 2013 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA), 23-29, Piscataway, N.J., DOI: 10.1109/CISDA.2013.6595423.
  • Hingston, P., Ranjeet, T., Lam, P., Masek, M., (2012), A Multimodal Problem for Competitive Coevolution. Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence, 338-349, Heidelberg, DOI: 10.1007/978-3-642-35101-3_29.
  • Wittkamp, M., Barone, L., Hingston, P., While, L., (2012), Real-Ttme Evolutionary Learning of Cooperative Predator-Prey Strategies. Proceedings of the Thirty-Fifth Australasian Computer Science Conference (ACSC 2012), 122(30 January - 3 February 2012), 81-90, Sydney, NSW.
  • Wittkamp, M., Barone, L., Hingston, P., While, L., (2012), Noise Tolerance for Real-time Evolutionary Learning of Cooperative Predator-Prey Strategies. 2012 IEEE Conference on Computational Intelligence and Games (CIG), 25-32, Piscataway, N.J..
  • Beard, D., Hingston, P., Masek, M., (2012), Using Monte Carlo Tree Search for Replanning in a Multistage Simultaneous Game. Proceedings of 2012 IEEE Congress on Evolutionary Computation, 1-8, Piscataway, NJ, USA.
  • Hingston, P., Preuss, M., (2011), Red teaming with coevolution. 2011 IEEE Congress on Evolutionary Computation, 1155-1163, Piscataway, NJ, USA, DOI: 10.1109/CEC.2011.5949747.
  • Zeng, F., Decraene, J., Low, MY., Cai, W., Hingston, P., (2011), Studies on Pareto-based multi-objective Competitive Coevolutionary Dynamics. Proceedings of the IEEE Congress on Evolutionary Computation, 2383-2390, Piscataway, NJ, USA, DOI: 10.1109/CEC.2011.5949912.
  • Ranjeet, T., Masek, M., Hingston, P., Lam, P., (2011), The effects of diversity maintenance on coevolution for an intransitive numbers problem. AI 2011: Advances in Artificial Intelligence. 24th Australasian Joint Conference. Proceedings, 7106 LNAI(5-8 December 2011 ), 331-340, Germany, DOI: 10.1007/978-3-642-25832-9_34.
  • Fanchao, Z., Decraene, J., Low, M., Cai, W., Zhou, S., Hingston, P., (2011), High-dimensional Objective-based Data Farming., 80-87, Piscataway, NJ, USA.
  • Ranjeet, T., Hingston, P., Lam, P., Masek, M., (2011), Analysis of Key Installation Protection using Computerized Red Teaming. Thirty-Fourth Australasian Computer Science Conference, 113(January 2011),  137-144,  Perth, Australia.

Research Student Supervision

Principal Supervisor

  • Doctor of Philosophy,  Intelligent Network Intrusion Detection Using An Evolutionary Computation Approach
  • Doctor of Philosophy,  On The Recognition Of Emotion From Physiological Data
  • Doctor of Information Technology,  A Feedback Control System For Exergames.

Co-principal Supervisor

  • Doctor of Information Technology,  Coevolutionary Algorithms For The Optimization Of Strategies For Red Teaming Applications

Associate Supervisor

  • Doctor of Information Technology,  An Investigation Into The Use Of Neural Networks For The Prediction Of The Stock Exchange Of Thailand.
Skip to top of page