“Modelling and Understanding Cooperation in Societies of Artificial Agents”
25th November 2021, 11am-12pm GMT
In this seminar, Marco will discuss the design of reinforcement learning architectures composed of autonomous agents that do not rely on centralised coordination. He will introduce examples of applications of machine learning algorithms to social dilemmas and cooperative games.
The analysis and modelling of the evolution of cooperation in competitive environments are of interest for economics, game theory, biology, psychology, and computer science just to name a few. Mathematical and computational models have been developed in order to extract insights on the underlying mechanisms. More recently, there has been an increasing interest in the study of societies based on artificial agents that can learn their strategies as they interact. The applications of this work are many: from the design of self-organising agent systems, including robotic ones, to the understanding of the emergence of cooperation in human and animal societies (and, possibly, in the future, in mixed environments composed of humans and artificial agents).
Bio
Mirco Musolesi is Full Professor of Computer Science at the Department of Computer Science at University College London and a Turing Fellow at the Alan Turing Institute, the UK National Institute for Data Science and Artificial Intelligence. He is also Full Professor of Computer Science at the University of Bologna. Previously, he held research and teaching positions at Dartmouth, Cambridge, St Andrews and Birmingham. The focus of his lab is on Machine Learning/Artificial Intelligence and their applications to a variety of practical and theoretical problems and domains, in particular networked systems, human-centred AI, computational social science and security&privacy. More information about his research profile can be found at: https://www.mircomusolesi.org
No registration required, join via Zoom:https://qmul-ac-uk.zoom.us/j/81148100921