Playout Search for Monte-Carlo Tree Search in Multi-player Games
نویسندگان
چکیده
Monte-Carlo Tree Search (MCTS) has become a popular search technique for playing multi-player games over the past few years. In this paper we propose a technique called Playout Search. This enhancement allows the use of small searches in the playout phase of MCTS in order to improve the reliability of the playouts. We investigate max, Paranoid and BRS for Playout Search and analyze their performance in two deterministic perfect-information multi-player games: Focus and Chinese Checkers. The experimental results show that Playout Search significantly increases the quality of the playouts in both games. However, it slows down the speed of the playouts, which outweighs the benefit of better playouts if the thinking time for the players is small. When the players are given a sufficient amount of thinking time, Playout Search employing Paranoid search is a significant improvement in the 4-player variant of Focus and the 3-player variant of Chinese Checkers.
منابع مشابه
Efficient Sampling Method for Monte Carlo Tree Search Problem
We consider Monte Carlo tree search problem, a variant of Min-Max tree search problem where the score of each leaf is the expectation of some Bernoulli variables and not explicitly given but can be estimated through (random) playouts. The goal of this problem is, given a game tree and an oracle that returns an outcome of a playout, to find a child node of the root which attains an approximate m...
متن کاملNested Monte Carlo Search for Two-Player Games
The use of the Monte Carlo playouts as an evaluation function has proved to be a viable, general technique for searching intractable game spaces. This facilitate the use of statistical techniques like Monte Carlo Tree Search (MCTS), but is also known to require significant processing overhead. We seek to improve the quality of information extracted from the Monte Carlo playout in three ways. Fi...
متن کاملEnhancements for Multi-Player Monte-Carlo Tree Search
Monte-Carlo Tree Search (MCTS) is becoming increasingly popular for playing multi-player games. In this paper we propose two enhancements for MCTS in multi-player games: (1) Progressive History and (2) Multi-Player Monte-Carlo Tree Search Solver (MP-MCTS-Solver). We analyze the performance of these enhancements in two different multi-player games: Focus and Chinese Checkers. Based on the experi...
متن کاملPlayout Policy Adaptation for Games
Monte Carlo Tree Search (MCTS) is the state of the art algorithm for General Game Playing (GGP). We propose to learn a playout policy online so as to improve MCTS for GGP. We test the resulting algorithm named Playout Policy Adaptation (PPA) on Atarigo, Breakthrough, Misere Breakthrough, Domineering, Misere Domineering, Go, Knightthrough, Misere Knightthrough, Nogo and Misere Nogo. For most of ...
متن کاملA Parallel Monte-Carlo Tree Search Algorithm
Monte-Carlo tree search is a powerful paradigm for the game of Go. We present a parallel Master-Slave algorithm for Monte-Carlo tree search. We experimented the algorithm on a network of computers using various configurations: from 12,500 to 100,000 playouts, from 1 to 64 slaves, and from 1 to 16 computers. On our architecture we obtain a speedup of 14 for 16 slaves. With a single slave and fiv...
متن کامل