Showing papers by "Neil Burch published in 2007"

Checkers Is Solved

Abstract: The game of checkers has roughly 500 billion billion possible positions (5 × 1020). The task of solving the game, determining the final result in a game with no mistakes made by either player, is daunting. Since 1989, almost continuously, dozens of computers have been working on solving checkers, applying state-of-the-art artificial intelligence techniques to the proving process. This paper announces that checkers is now solved: Perfect play by both sides leads to a draw. This is the most challenging popular game to be solved to date, roughly one million times as complex as Connect Four. Artificial intelligence technology has been used to generate strong heuristic-based game-playing programs, such as Deep Blue for chess. Solving a game takes this to the next level by replacing the heuristics with perfection.

A new algorithm for generating equilibria in massive zero-sum games

Abstract: In normal scenarios, computer scientists often consider the number of states in a game to capture the difficulty of learning an equilibrium. However, players do not see games in the same light: most consider Go or Chess to be more complex than Monopoly. In this paper, we discuss a new measure of game complexity that links existing state-of-the-art algorithms for computing approximate equilibria to a more human measure. In particular, we consider the range of skill in a game, i.e. how many different skill levels exist. We then modify existing techniques to design a new algorithm to compute approximate equilibria whose performance can be captured by this new measure. We use it to develop the first near Nash equilibrium for a four round abstraction of poker, and show that it would have been able to win handily the bankroll competition from last year's AAAI poker competition.