Case-based strategies in computer poker
Author:
Affiliation:
1. Department of Computer Science, University of Auckland Game AI Group, Auckland, New Zealand. E-mails: jrubin01@gmail.com, ian@cs.auckland.ac.nz
Publisher
IOS Press
Subject
Artificial Intelligence
Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Investigating Cases and Clusters-Based Reuse Policies for Card-Playing Agents;2023 IEEE Conference on Games (CoG);2023-08-21
2. Active Learning and Case-Based Reasoning for the Deceptive Play in the Card Game of Truco;Intelligent Systems;2021
3. Investigating Case Learning Techniques for Agents to Play the Card Game of Truco;2020 19th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames);2020-11
4. Cases and Clusters in Reuse Policies for Decision-Making in Card Games;2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI);2019-11
5. What's the Next Move? Learning Player Strategies in Zoom Poker Games;2018 IEEE Congress on Evolutionary Computation (CEC);2018-07
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