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Card Games

Card games involve playing cards: the task is to train an agent to play the game with specified rules and beat other players.

Papers

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Showing 26–50 of 52 papers

TitleStatusHype
Policy Based Inference in Trick-Taking Card Games—0
Procedural Content Generation via Machine Learning (PCGML)—0
Reinforcement Learning for Hanabi—0
Riffled Independence for Ranked Data—0
SPIN-Bench: How Well Do LLMs Plan Strategically and Reason Socially?—0
The Many AI Challenges of Hearthstone—0
Towards Modern Card Games with Large-Scale Action Spaces Through Action Representation—0
Transformer Based Planning in the Observation Space with Applications to Trick Taking Card Games—0
Aggregated Semantic Matching for Short Text Entity Linking—0
Improving Search with Supervised Learning in Trick-Based Card Games—0
Introducing the Hearthstone-AI Competition—0
Knowledge-Based Paranoia Search in Trick-Taking—0
Learning Policies from Human Data for Skat—0
Learning to Beat ByteRL: Exploitability of Collectible Card Game Agents—0
Learning With Generalised Card Representations for "Magic: The Gathering"—0
Identifying and Clustering Counter Relationships of Team Compositions in PvP Games for Efficient Balance AnalysisCode0
RLCard: A Toolkit for Reinforcement Learning in Card GamesCode0
Enhancing Commentary Strategies for Imperfect Information Card Games: A Study of Large Language Models in Guandan CommentaryCode0
Analysis of Evolutionary Program Synthesis for Card GamesCode0
Predicting Human Card Selection in Magic: The Gathering with Contextual Preference RankingCode0
Combinational Q-Learning for Dou Di ZhuCode0
Survey of Artificial Intelligence for Card Games and Its Application to the Swiss Game JassCode0
Approximating Poker Probabilities with Deep LearningCode0
Q-DeckRec: A Fast Deck Recommendation System for Collectible Card GamesCode0
Application of Self-Play Reinforcement Learning to a Four-Player Game of Imperfect InformationCode0
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