Playing Board Games with the Predict Results of Beam Search Algorithm

TMLR Paper3413 Authors

Abstract:

This paper introduces a novel algorithm for two-player deterministic games with perfect
information, which we call PROBS (Predict Results of Beam Search). Unlike existing meth-
ods that predominantly rely on Monte Carlo Tree Search (MCTS) for decision processes,
our approach leverages a simpler beam search algorithm. We evaluate the performance
of our algorithm across a selection of board games, where it consistently demonstrates an
increased winning ratio against baseline opponents. A key result of this study is that the
PROBS algorithm operates effectively, even when the beam search depth is considerably
smaller than the average number of turns in the game

Submission Length: Regular submission (no more than 12 pages of main content)

Changes Since Last Submission:

1). Adapted TMLR LaTeX template
2). Removed author names

Assigned Action Editor: ~Dennis_J._N._J._Soemers1

Submission Number: 3413