Regular Boardgames

We propose a new General Game Playing (GGP) language called Regular Boardgames (RBG), which is based on the theory of regular languages. The objective of RBG is to join key properties as expressiveness, efficiency, and naturalness of the description in one GGP formalism, compensating certain drawbacks of the existing languages. This often makes RBG more suitable for various research and practical developments in GGP. While dedicated mostly for describing board games, RBG is universal for the class of all finite deterministic turn-based games with perfect information. We establish foundations of RBG, and analyze it theoretically and experimentally, focusing on the efficiency of reasoning. Regular Boardgames is the first GGP language that allows efficient encoding and playing games with complex rules and with large branching factor (e.g.\ amazons, arimaa, large chess variants, go, international checkers, paper soccer).Comment: AAAI 201

KQQKQQ and the Kasparov-World Game

The 1999 Kasparov-World game for the first time enabled anyone to join a team playing against a World Chess Champion via the web. It included a surprise in the opening, complex middle-game strategy and a deep ending. As the game headed for its mysterious finale, the World Team re-quested a KQQKQQ endgame table and was provided with two by the authors. This paper describes their work, compares the methods used, examines the issues raised and summarises the concepts involved for the benefit of future workers in the endgame field. It also notes the contribution of this endgame to chess itself

Chicken or Checkin'? Rational Learning in Repeated Chess Games

We examine rational learning among expert chess players and how they update their beliefs in repeated games with the same opponent. We present a model that explains how equilibrium play is affected when players change their choice of strategy when receiving additional information from each encounter. We employ a large international panel dataset with controls for risk preferences and playing skills whereby the latter accounts for ability. Although expert chess players are intelligent, productive and equipped with adequate data and specialized computer programs, we find large learning effects. Moreover, as predicted by the model, risk-averse players learn substantially faster.risk aversion, rational learning, beliefs

On the Domination Chain of m by n Chess Graphs

A survey of the six domination chain parameters for both square and rectangular chess boards are discussed