Evolving agent decision-making in social-technical systems
The overarching goal of this project is to investigate agent decision-making in coupled social-technical systems. An evolutionary game theoretic framework will be used to build computational models of multi-player game scenarios, where individual agents are faced with a social dilemma — a situation where individuals have to select between short-term personal profits and long-term social benefits. Numerical simulations will be combined with analytical analysis to explore emergent agent behaviour.
This framework will be used to validate new conceptual approaches for coordination and cooperation in areas of computing where forms of advanced social behaviour are becoming increasingly significant.
Leader: Michael Kirley
Collaborators: Yoshi Kashima (School of Psychological Sciences)
Sponsors: Australian Research Council
Computing and Information Systems
Networks and data in society
agent based systems; artificial intelligence; evolutionary algorithms