Generalized Rapid Action Value Estimation

Tristan Cazenave (1)

1 LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision

Monte Carlo Tree Search (MCTS) is the state of the art algorithm for many games including the game of Go and General Game Playing (GGP). The standard algorithm for MCTS is Upper Confidence bounds applied to Trees (UCT). For games such as Go a big improvement over UCT is the Rapid Action Value Estimation (RAVE) heuristic. We propose to generalize the RAVE heuristic so as to have more accurate estimates near the leaves. We test the resulting algorithm named GRAVE for Atarigo, Knighthrough, Domineering and Go.

Mots clés: Monte Carlo Tree Search

Domaines: Informatique [cs]

Tristan Cazenave. Generalized Rapid Action Value Estimation. 24th International Conference on Artificial Intelligence, Jul 2015, Buenos Aires, Argentina. pp.754-760. ⟨hal-01436522⟩