Abstract— This paper describes experiments using reinforcement learning techniques to compute pattern urgencies used during simulations performed in a Monte-Carlo Go architecture...
Abstract-- We present and explore the effectiveness of several variations on the All-Moves-As-First (AMAF) heuristic in Monte-Carlo Go. Our results show that:
In the last decade, proof-number search and Monte-Carlo methods have successfully been applied to the combinatorial-games domain. Proof-number search is a reliable algorithm. It re...
Jahn-Takeshi Saito, Guillaume Chaslot, Jos W. H. M...
We present a way to integrate search and Monte-Carlo methods in the game of Go. Our program uses search to find the status of tactical goals, builds groups, selects interesting go...
Abstract. Progressive Pruning (PP) is used in the Monte-Carlo go playing program Indigo. For each candidate move, PP launches random games starting with this move. PP gathers stati...