Designing Card Game Strategies with Genetic Programming and Monte-Carlo Tree Search: A Case Study of Hearthstone

Hao Cheng Chia, Tsung Su Yeh, Tsung Che Chiang

研究成果: 書貢獻/報告類型會議論文篇章

摘要

This paper addresses an agent design problem of a digital collectible card game, Hearthstone, which is a two-player turn-based game. The agent has to play cards based on the game state, the hand cards, and the deck of cards to defeat the opponent. First, we design a rule-based agent by searching for the board evaluation criterion through genetic programming (GP). Then, we integrate the rule-based agent into the Monte-Carlo tree search (MCTS) framework to generate an advanced agent. Performance of the proposed agents are verified by playing against three participants in two recent Hearthstone competitions. Experimental results showed that the GP-agent can beat a simple MCTS agent and the mid-level agent in the competition. The MCTS-GP agent showed competitive performance against the best agents in the competition. We also examine the rule found by GP and observed that GP is able to identify key attributes of game states and to combine them into a useful rule automatically.

原文英語
主出版物標題2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
發行者Institute of Electrical and Electronics Engineers Inc.
頁面2351-2358
頁數8
ISBN(電子)9781728125473
DOIs
出版狀態已發佈 - 2020 十二月 1
事件2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 - Virtual, Canberra, 澳大利亚
持續時間: 2020 十二月 12020 十二月 4

出版系列

名字2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020

會議

會議2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
國家澳大利亚
城市Virtual, Canberra
期間2020/12/012020/12/04

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Decision Sciences (miscellaneous)

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