Associate Professor Michael Kirley

  • Room: Level: 06 Room: 608
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Artificial Intelligence (Machine learning; Reinforcement learning)
  • Complex Adaptive Systems (Nonlinear dynamical systems)
  • Evolutionary Computation (Algorithms; Metaheuristics; Optimisation)
  • Evolutionary Game Theory (Cooperation; Cultural dynamics)
  • Multi-Agent Systems (Autonomous agents; Simulation)

Biography

Dr Michael Kirley is a member of the academic staff at The University of Melbourne, where he holds an appointment as an Associate Professor in the School of Computing and Information Systems within the Melbourne School of Engineering.

Michael's research is focussed on understanding complex adaptive systems, where the overarching goal is to develop an interdisciplinary synthesis describing evolutionary processes in both natural and artificial systems. His main scientific contributions are in three areas:

  • First, in the analysis and design of evolutionary algorithms; including exploratory landscape analysis with applications in large-scale, open and dynamic environments.
  • Second, developing new mechanisms and algorithms, inspired by evolutionary game theory, to explore the evolution of social behaviours such as cooperation and cultural dynamics.
  • Third, combining computational and agent-based software engineering methodologies to build robust simulation models of complex social-ecological systems.

Michael has received multiple awards for excellence in both teaching and research:

  • Excellence in Research 2009, Department of Computer Science and Software Engineering, The University of Melbourne
  • Excellence in Teaching 2011, Department of Computer Science and Software Engineering, The University of Melbourne
  • Teaching Excellence 2005, Faculty of Engineering, The University of Melbourne
  • Excellence in Teaching 2004, Department of Computer Science and Software Engineering, The University of Melbourne

Recent publications

  1. Zhu, H.; Kirley, M. Deep Multi-agent Reinforcement Learning in a Common-Pool Resource System. 2019 IEEE Congress on Evolutionary Computation (CEC). IEEE. 2019, pp. 142-149. DOI: 10.1109/CEC.2019.8790001
  2. Herring, D.; Kirley, M.; Yao, X. Investigation of Asynchrony in Dynamic Multi-Objective Optimization. 2019 IEEE Congress on Evolutionary Computation (CEC). IEEE. 2019, pp. 3165-3172. DOI: 10.1109/CEC.2019.8790270
  3. Shank, DB.; Kashima, Y.; Peters, K.; Li, Y.; Robins, G.; Kirley, M. Norm Talk and Human Cooperation: Can We Talk Ourselves Into Cooperation?. Journal of Personality and Social Psychology. AMER PSYCHOLOGICAL ASSOC. 2019, Vol. 117, Issue 1, pp. 99-123. DOI: 10.1037/pspi0000163
  4. Chica, M.; Chiong, R.; Kirley, M.; Ishibuchi, H. A Networked N-Player Trust Game and Its Evolutionary Dynamics. IEEE Transactions on Evolutionary Computation. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. 2018, Vol. 22, Issue 6, pp. 866-878. DOI: 10.1109/TEVC.2017.2769081
  5. Sun, Y.; Kirley, M.; Halgamuge, SK. A Recursive Decomposition Method for Large Scale Continuous Optimization. IEEE Transactions on Evolutionary Computation. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. 2018, Vol. 22, Issue 5, pp. 647-661. DOI: 10.1109/TEVC.2017.2778089
  6. Sun, Y.; Kirley, M.; Omidvar, MN.; Li, X. Adaptive threshold parameter estimation with recursive differential grouping for problem decomposition. Proceedings of the Genetic and Evolutionary Computation Conference on - GECCO '18. Association for Computing Machinery (ACM). 2018, pp. 889-896. DOI: 10.1145/3205455.3205483
  7. Ku, YK.; Kirley, M.; Karakiewicz, J.; Jiang, YM. Conceptualizing the evolution of Tmor-Da. Blucher Design Proceedings. Editora Blucher. 2018, pp. 238-244. DOI: 10.5151/sigradi2018-1413
  8. Sun, Y.; Kirley, M.; Li, X. Cooperative Co-evolution with online optimizer selection for large-scale optimization. Proceedings of the Genetic and Evolutionary Computation Conference on - GECCO '18. Association for Computing Machinery (ACM). 2018, pp. 1079-1086. DOI: 10.1145/3205455.3205625
  9. Sun, Y.; Kirley, M.; Halgamuge, SK. A Memetic Cooperative Co-evolution Model for Large Scale Continuous Optimization. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). SPRINGER INTERNATIONAL PUBLISHING AG. 2017, Vol. 10142, pp. 291-300. DOI: 10.1007/978-3-319-51691-2_25
  10. Cruz, C.; Kirley, M.; Karakiewicz, J. An interactive approach for evolving pareto optimal architectural form. Simulation Series. Society for Computer Simulation International. 2017, Vol. 49, Issue 11, pp. 33-40.
  11. Cruz, C.; Kirley, M.; Karakiewicz, J. Generation and Exploration of Architectural Form Using a Composite Cellular Automata. . 0302-9743. 2017.
  12. Cruz, C.; Kirley, M.; Karakiewicz, J. Generation and exploration of architectural form using a composite cellular automata. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer International Publishing. 2017, Vol. 10142 LNAI, pp. 99-110. DOI: 10.1007/978-3-319-51691-2_9
  13. Kashima, Y.; Kirley, M.; Stivala, A.; Robins, G. Modeling cultural dynamics. . Routledge. 2017, pp. 281-307. DOI: 10.4324/9781315173726
  14. Sun, Y.; Kirley, M.; Halgamuge, SK. Quantifying Variable Interactions in Continuous Optimization Problems. IEEE Transactions on Evolutionary Computation. IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. 2017, Vol. 21, Issue 2, pp. 249-264. DOI: 10.1109/TEVC.2016.2599164
  15. Von Der Osten, FB.; Kirley, M.; Miller, T. Sustainability is possible despite greed - Exploring the nexus between profitability and sustainability in common pool resource systems. Scientific Reports. NATURE PUBLISHING GROUP. 2017, Vol. 7, Issue 1. DOI: 10.1038/s41598-017-02151-y
  16. Von Der Osten, FB.; Kirley, M.; Miller, T. The minds of many: Opponent modelling in a stochastic game. IJCAI International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence. 2017, pp. 3845-3851.
  17. Cruz, C.; Karakiewicz, J.; Kirley, M. A Morphogenetic Design Strategy Using a Composite CA Model. Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion - GECCO '16 Companion. ASSOC COMPUTING MACHINERY. 2016, pp. 17-18. DOI: 10.1145/2908961.2909058
  18. Varmazyar, M.; Haritos, N.; Kirley, M. A wavelet-based Bayesian damage identification technique using an evolutionary algorithm. Australian Journal of Structural Engineering. TAYLOR & FRANCIS AS. 2016, Vol. 17, Issue 4, pp. 225-241. DOI: 10.1080/13287982.2016.1259712
  19. Stivala, A.; Kashima, Y.; Kirley, M. Culture and cooperation in a spatial public goods game. Physical Review E. AMER PHYSICAL SOC. 2016, Vol. 94, Issue 3. DOI: 10.1103/PhysRevE.94.032303
  20. Stivala, A.; Robins, G.; Kashima, Y.; Kirley, M. Diversity and Community Can Coexist. American Journal of Community Psychology. WILEY. 2016, Vol. 57, Issue 1-2, pp. 243-254. DOI: 10.1002/ajcp.12021

View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile