---
title: "Monte Carlo Tree Search Techniques in the Game of Kriegspiel"
authors:
  - "Paolo Ciancarini"
  - "Gian Piero Favini"
doi: ""
url: "https://ijcai.org/proceedings/2009/86"
pdf: "https://ijcai.org/proceedings/2009/0086.pdf"
venue: "Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence"
year: 2009
pages: "474-478"
track: ""
keywords:
---

# Monte Carlo Tree Search Techniques in the Game of Kriegspiel

Paolo Ciancarini, Gian Piero Favini

*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