Dr Daniel Kudenko (http://www.cs.york.ac.uk/~kudenko/) is a Lecturer in the Artificial Intelligence Group of the Computer Science Department at the University of York. His research is focused around machine learning (e.g, web data mining [TIN09]), user modelling, and artificial intelligence for games (e.g. interactive drama [BAR10]). He has published over 80 peer-reviewed papers in various areas of artificial intelligence, receiving a best paper nomination at the leading international evolutionary algorithms conference, GECCO'07, and a best paper award at the 2007 workshop on engineering Stochastic Local Search Algorithms (SLS'07). He has a strong record in knowledge transfer and collaboration with industry, working together on many projects with the MoD, QinetiQ and Eidos. He spent a full year on Industrial Secondment at Core Design Studios, sponsored by Eidos and the Royal Academy of Engineering, working on the transfer of AI research results to commercial computer game products. He was a coordinator for the AgentLink II European Network of Excellence and a member of its management committee, and has sat on numerous program committees for leading scientific conferences (including AAMAS, AAAI, ECAI, ICML, and IAT).