General game players are computer systems able to play strategy games based solely on formal game descriptions supplied at "runtime" (n other words, they don't know the rules until the game starts). Unlike specialized game players, such as Deep Blue, general game players cannot rely on algorithms designed in advance for specific games; they must discover such algorithms themselves. General game playing expertise depends on intelligence on the part of the game player and not just intelligence of the programmer of the game player. GGP is an interesting application in its own right. It is intellectually engaging and more than a little fun. But it is much more than that. It provides a theoretical framework for modeling discrete dynamic systems and defining rationality in a way that takes into account problem representation and complexities like incompleteness of information and resource bounds. It has practical applications in areas where these features are important, e.g., in business andlaw. More fundamentally, it raises questions about the nature of intelligence and serves as a laboratory in which to evaluate competing approaches to artificial intelligence. This book is an elementary introduction to General Game Playing (GGP). (1) It presents the theory of General Game Playing and leading GGP technologies. (2) It shows how to create GGP programs capable of competing against other programs and humans. (3) It offers a glimpse of some of the real-world applications of General Game Playing.

Autorentext

Michael Genesereth is a professor in the Computer Science Department at Stanford University and a professor by courtesy in the Stanford Law School. He received his Sc.B. in Physics from M.I.T. and his Ph.D. in Applied Mathematics from Harvard University. Genesereth is most known for his work on Computational Logic and applications of that work in Enterprise Management, Computational Law, and General Game Playing. He is one of the founders of Teknowledge, CommerceNet, Mergent Systems, and Symbium. Genesereth is the current director of the Logic Group at Stanford and co-founder and research director of CodeX (the Stanford Center for Legal Informatics).Vinay K. Chaudhri is formerly a program director in the Artificial Intelligence Center at SRI International, and currently affiliated with the Stanford Computer Science Department. He received his Ph.D. in Computer Science from University of Toronto, Canada. Dr. Chaudhri is arecognized expert on artificial intelligence, including knowledgerepresentation and reasoning, question answering, ontologies, and knowledge acquisition. At Stanford his activities include promoting logic education for secondary schools, investigating techniques for rapidly acquiring formal knowledge and productizing intelligent textbooks. He consults with the financial industry on computable contracts and knowledge graphs. He has also taught courses on knowledge representation and reasoning and logic programming.

Inhalt
Preface.- Introduction.- Game Description.- Game Management.- Game Playing.- Small Single-Player Games.- Small Multiple-Player Games.- Heuristic Search.- Probabilistic Search.- Propositional Nets.- General Game Playing With Propnets.- Factoring.- Discovery of Heuristics.- Logic.- Analyzing Games with Logic.- Solving Single-Player Games with Logic.- Discovering Heuristics with Logic.- Games with Incomplete Information.- Games with Historical Constraints.- Incomplete Game Descriptions.- Advanced General Game Playing.- Authors' Biographies.