Monte Carlo Tree Search Techniques in the Game of Kriegspiel
Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence. Pages 474-478.
Abstract
Monte Carlo tree search has brought significant improvements to the level of computer players in games such as Go, but so far it has not been used very extensively in games of strongly imperfect information with a dynamic board and an emphasis on risk management and decision making under uncertainty. In this paper we explore its application to the game of Kriegspiel (invisible chess), providing three Monte Carlo methods of increasing strength for playing the game with little specific knowledge. We compare these Monte Carlo agents to the strongest known minimax-based Kriegspiel player, obtaining significantly better results with a considerably simpler logic and less domain-specific knowledge.Paolo Ciancarini, Gian Piero Favini
@inproceedings{ijcai2009p86,
title = {Monte Carlo Tree Search Techniques in the Game of Kriegspiel},
author = {Ciancarini, Paolo and Favini, Gian Piero},
booktitle = {Proceedings of the Twenty-First International Joint Conference on
Artificial Intelligence, {IJCAI-09}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Hiroaki Kitano},
pages = {474--478},
year = {2009},
url = {https://ijcai.org/proceedings/2009/86},
}
TY - CPAPER TI - Monte Carlo Tree Search Techniques in the Game of Kriegspiel AU - Ciancarini, Paolo AU - Favini, Gian Piero T2 - Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence, IJCAI-09 PB - International Joint Conferences on Artificial Intelligence PY - 2009 SP - 474 EP - 478 UR - https://ijcai.org/proceedings/2009/86 ER -Copied
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