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Card Games
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Card games involve playing cards: the task is to train an agent to play the game with specified rules and beat other players.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/RuBP17/AlphaDou
공식 코드AlphaDou: High-Performance End-to-End Doudizhu AI Integrating Bidding
https://github.com/Tibert97/Predicting-Human-Card-Selection-in-Magic-The-Gathering-with-Contextual-Preference-Ranking
공식 코드Predicting Human Card Selection in Magic: The Gathering with Contextual Preference Ranking
https://github.com/WuTheFWasThat/hanabi.rs
공식 코드Improving Policies via Search in Cooperative Partially Observable Games
https://github.com/brandinho/Poker-Probability-Approximation
공식 코드https://github.com/chandar-lab/adaptive-hanabi
공식 코드Towards Few-shot Coordination: Revisiting Ad-hoc Teamplay Challenge In the Game of Hanabi
https://github.com/cr-gjx/suspicion-agent
공식 코드Suspicion-Agent: Playing Imperfect Information Games with Theory of Mind Aware GPT-4
https://github.com/datamllab/rlcard
공식 코드https://github.com/deepmind/card2code
공식 코드https://github.com/facebookresearch/Hanabi_SPARTA
공식 코드Improving Policies via Search in Cooperative Partially Observable Games
https://github.com/fergunet/SabberStone
공식 코드Optimizing Hearthstone Agents using an Evolutionary Algorithm
https://github.com/heimy2000/guandan
공식 코드https://github.com/henrycharlesworth/big2_PPOalgorithm
공식 코드Application of Self-Play Reinforcement Learning to a Four-Player Game of Imperfect Information
https://github.com/jinhaoduan/gtbench
공식 코드GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations
https://github.com/kwai/DouZero
공식 코드DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning
https://github.com/martinballa/pytag
공식 코드PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games
https://github.com/pdturney/open-ended-immigration-games
공식 코드https://github.com/qq456cvb/doudizhu-C
공식 코드https://github.com/scriptsoftribute/scriptsoftribute-core
공식 코드https://github.com/simpleParadox/CMPUT-659-Project
공식 코드https://github.com/stelios30/aamas23-responsibility-attribution-mcts
공식 코드https://github.com/submit-paper/Danzero_plus
공식 코드DanZero+: Dominating the GuanDan Game through Reinforcement Learning
https://github.com/thecharlieblake/Solvitaire
공식 코드The Winnability of Klondike Solitaire and Many Other Patience Games
https://github.com/zayenz/cp-2019-nmbr9
공식 코드https://github.com/Branbados/rlcard
https://github.com/Dominik1999/SchafkopfAI
Survey of Artificial Intelligence for Card Games and Its Application to the Swiss Game Jass
https://github.com/EricSteinberger/DREAM
Deep Reinforcement Learning from Self-Play in Imperfect-Information Games
https://github.com/IAARhub/TrucoAnalytics
Deep Reinforcement Learning from Self-Play in Imperfect-Information Games
https://github.com/Theomat/hanabi-enseirb-2020
Improving Policies via Search in Cooperative Partially Observable Games
https://github.com/TinkeringCode/Neural-Fictitous-Self-Play
Deep Reinforcement Learning from Self-Play in Imperfect-Information Games
https://github.com/XiangboGaoBarry/TexasHoldemAI
https://github.com/Yuta123456/poker-ai
https://github.com/chandar-lab/RLHive
https://github.com/cogitoergoread/rlcard3
https://github.com/czxttkl/X-AI
Q-DeckRec: A Fast Deck Recommendation System for Collectible Card Games
https://github.com/datamllab/rlcard-tutorial
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.