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MCTS Based Agents for Multistage Single-Player Card Game

Artificial Intelligence 2021-09-28 v1 Machine Learning

Abstract

The article presents the use of Monte Carlo Tree Search algorithms for the card game Lord of the Rings. The main challenge was the complexity of the game mechanics, in which each round consists of 5 decision stages and 2 random stages. To test various decision-making algorithms, a game simulator has been implemented. The research covered an agent based on expert rules, using flat Monte-Carlo search, as well as complete MCTS-UCB. Moreover different playout strategies has been compared. As a result of experiments, an optimal (assuming a limited time) combination of algorithms were formulated. The developed MCTS based method have demonstrated a advantage over agent with expert knowledge.

Keywords

Cite

@article{arxiv.2109.12112,
  title  = {MCTS Based Agents for Multistage Single-Player Card Game},
  author = {Konrad Godlewski and Bartosz Sawicki},
  journal= {arXiv preprint arXiv:2109.12112},
  year   = {2021}
}

Comments

Published in 2020 IEEE 21st International Conference on Computational Problems of Electrical Engineering. arXiv admin note: text overlap with arXiv:2109.12001

R2 v1 2026-06-24T06:18:23.394Z