Title: Co-evolutionary Learning in Game-Playing
Abstract: Co-evolution has been used widely in automatic learning of game-playing strategies, e.g., for iterated prisoner's dilemma games, backgammon, chess, etc. It is a very interesting form of learning because it learns by interactions only, without any explicit target output information. In other words, the correct choices or moves were not provided as teacher information in learning. Yet co-evolutionary learning is still able to learn high-performance, in comparison to average human performance, game-playing strategies. Interestingly, the research of co-evolutionary learning has not focused on its generalisation ability, in sharp contrast to machine learning in general, where generalisation is at the heart of learning of any form. This talk presents one of the few generic frameworks that are available for measuring generalisation of co- evolutionary learning. It enables us to discuss and study generalisation of different co-evolutionary algorithms more objectively and quantitatively. As a result, it enables us to draw more appropriate conclusions about the abilities of our learned game-playing strategies in dealing with totally new and unseens environments (including opponents). The iterated prisoner's dilemma game will be used as an example in this talk to illustrate our theoretical framework and performance improvements we could gain by following this more principled approach to co-evolutionary learning.
Xin Yao is a Chair (Professor) of Computer Science and the Director of CERCIA (Centre of Excellence for Research in Computational Intelligence and Applications) at the University of Birmingham, UK. He is an IEEE Fellow and the President (2014-15) of IEEE Computational Intelligence Society (CIS). His work won the 2001 IEEE Donald G. Fink Prize Paper Award, 2010 IEEE Transactions on Evolutionary Computation Outstanding Paper Award, 2010 BT Gordon Radley Award for Best Author of Innovation (Finalist), 2011 IEEE Transactions on Neural Networks Outstanding Paper Award, and many other best paper awards. He won the prestigious Royal Society Wolfson Research Merit Award in 2012 and the 2013 IEEE CIS Evolutionary Computation Pioneer Award. He was the Editor-in-Chief (2003-08) of IEEE Transactions on Evolutionary Computation. His major research interests include co-evolutionary computation, especially on competitive co- evolution for learning game-playing strategies and on cooperative co-evolution for large scale global optimisation. He also used co-evolution for evolving artificial neural networks and for automatic programming in software development, especially in software engineering.