SP2

New Trends in General Game Playing
Michael Thielscher

General Game Playing (GGP) is concerned with the development of systems that can play well an arbitrary game solely by being given the rules of the game. GGP has recently been proposed as one of the grand contemporary AI challenges, which encompasses a variety of research areas including

- Knowledge Representation and Reasoning

- Heuristic Search and Planning

- Computational Game Theory

- Learning

GGP has a number of immediate potential applications, including universal game computers, autonomous trading agents, and advice takers for economic decision problems.

This tutorial gives an introduction to the foundations of GGP systems and provides an in-depth insight into recent results, state-of-the-art techniques, and current and future research trends and developments.

The tutorial is directed at every AI researcher who wants to gain an insight into General Game Playing as a new, grand AI challenge, and who wants to learn about the key techniques, latest results, and current research trends in the design of GGP systems. The only required background is some basic knowledge of standard first-order logic.

Michael Thielscher is a professor at Dresden University and head of the Computational Logic Group. Michael's current research is mainly in knowledge representation, cognitive agents, game playing, and constraint logic programming. He has published over 70 refereed papers and four books, and he has co-authored the general game playing system FLUXPLAYER, which in 2006 has won the AAAI General Game Playing Contest.

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