Computers and Games

1. Front Matter

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2. Part 1: Evaluation and Learning

   1. Distinguishing Gamblers from Investors at the Blackjack Table

      • David Wolfe

      Pages 1-10

   2. MOUSE(μ): A Self-teaching Algorithm that Achieved Master-Strength at Othello

      • Konstantinos Tournavitis

      Pages 11-28

   3. Investigation of an Adaptive Cribbage Player

      • Graham Kendall, Stephen Shaw

      Pages 29-41

   4. Learning a Game Strategy Using Pattern-Weights and Self-play

      • Ari Shapiro, Gil Fuchs, Robert Levinson

      Pages 42-60

3. Part 2: Search

   1. PDS-PN: A New Proof-Number Search Algorithm

      • Mark H. M. Winands, Jos W. H. M. Uiterwijk, Jaap van den Herik

      Pages 61-74

   2. A Generalized Threats Search Algorithm

      • Tristan Cazenave

      Pages 75-87

   3. Proof-Set Search

      • Martin Müller

      Pages 88-107

   4. A Comparison of Algorithms for Multi-player Games

      • Nathan Sturtevant

      Pages 108-122

   5. Selective Search in an Amazons Program

      • Henry Avetisyan, Richard J. Lorentz

      Pages 123-141

   6. Playing Games with Multiple Choice Systems

      • Ingo Althöfer, Raymond Georg Snatzke

      Pages 142-153

   7. The Neural MoveMap Heuristic in Chess

      • Levente Kocsis, Jos W. H. M. Uiterwijk, Eric Postma, Jaap van den Herik

      Pages 154-170

   8. Board Maps and Hill-Climbing for Opening and Middle Game Play in Shogi

      • Reijer Grimbergen, Jeff Rollason

      Pages 171-187

4. Part 3: Combinatorial Games/Theory

   1. Solitaire Clobber

      • Erik D. Demaine, Martin L. Demaine, Rudolf Fleischer

      Pages 188-200

   2. Complexity of Error-Correcting Codes Derived from Combinatorial Games

      • Aviezri S. Fraenkel, Ofer Rahat

      Pages 201-212

   3. Analysis of Composite Corridors

      • Teigo Nakamura, Elwyn Berlekamp

      Pages 213-229

5. Part 4: Opening/Endgame Databases

   1. New Winning and Losing Positions for 7×7 Hex

      • Jing Yang, Simon Liao, Miroslaw Pawlak

      Pages 230-248

   2. Position-Value Representation in Opening Books

      • Thomas R. Lincke

      Pages 249-263

   3. Indefinite Sequence of Moves in Chinese Chess Endgames

      • Haw-ren Fang, Tsan-sheng Hsu, Shun-chin Hsu

      Pages 264-279

6. Part 5: Commercial Games

   1. ORTS: A Hack-Free RTS Game Environment

      • Michael Buro

      Pages 280-291

The Computers and Games (CG) series began in 1998 with the objective of showcasing new developments in arti?cial intelligence (AI) research that used games as the experimental test-bed. The ?rst two CG conferences were held at Hamamatsu,Japan(1998,2000).ComputersandGames2002(CG2002)wasthe third event in this biennial series. The conference was held at the University of Alberta(Edmonton,Alberta,Canada),July25–27,2002.Theprogramconsisted of the main conference featuring refereed papers and keynote speakers, as well as several side events including the Games Informatics Workshop, the Agents in Computer Games Workshop, the Trading Agents Competition, and the North American Computer Go Championship. CG 2002 attracted 110 participants from over a dozen countries. Part of the successoftheconferencewasthatitwasco-locatedwiththeNationalConference of the American Association for Arti?cial Intelligence (AAAI), which began in Edmonton just as CG 2002 ended. The CG 2002 program had 27 refereed paper presentations. The papers ranged over a wide variety of AI-related topics including search, knowledge, learning, planning, and combinatorial game theory. Research test-beds included one-player games (blackjack, sliding-tile puzzles, Sokoban), two-player games (Amazons, awari, chess, Chinese chess, clobber, Go, Hex, Lines of Action, O- ello, shogi), multi-player games (Chinese checkers, cribbage, Diplomacy, hearts, spades), commercial games (role-playing games, real-time strategy games), and novel applications (Post’s Correspondence Problem).

• Computer
• algorithmic learning
• algorithms
• calculus
• combinatorics
• complexity
• computer games
• computers and games
• data mining
• database
• heuristics
• learning
• logic
• search algorithms
• search strategies
• data structures
• algorithm analysis and problem complexity

• Computing Science Department, University of Alberta, Edmonton, Canada

  Jonathan Schaeffer

• Department of Computing Science, University of Alberta, Edmonton, Canada

  Martin Müller

• School of Computer Science, Reykjavík University, Reykjavík, Iceland

  Yngvi Björnsson

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