Deep Barca: A Probabilistic Agent to Play the Game Battle Line

摘要

Recent years have seen an explosion of interest in "modern" board games. These differ from the "classic" games typically seen in Artificial Intelligence research (e.g. Chess, Checkers, Go) in that the modern games often have a large component of randomness or non-public information, making traditional game-tree methods infeasible Often, these modern games have an underlying mathematical structure that can be exploited. In this paper, we describe an intelligent agent to play the game Battle Line, which uses elements of theorem-proving and probability to play intelligently without utilizing game trees. The agent is superior to the only other known computer player of the game and plays at a level competitive with top human players.