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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 1–50 of 52 papers

TitleStatusHype
GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic EvaluationsCode3
DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement LearningCode2
Introducing Tales of Tribute AI CompetitionCode1
Suspicion-Agent: Playing Imperfect Information Games with Theory of Mind Aware GPT-4Code1
The Winnability of Klondike Solitaire and Many Other Patience GamesCode1
DanZero+: Dominating the GuanDan Game through Reinforcement LearningCode1
Drafting in Collectible Card Games via Reinforcement LearningCode1
Latent Predictor Networks for Code GenerationCode1
Deep Reinforcement Learning from Self-Play in Imperfect-Information GamesCode1
AlphaDou: High-Performance End-to-End Doudizhu AI Integrating BiddingCode1
PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop GamesCode1
Towards Computationally Efficient Responsibility Attribution in Decentralized Partially Observable MDPsCode0
Identifying and Clustering Counter Relationships of Team Compositions in PvP Games for Efficient Balance AnalysisCode0
Analysis of Evolutionary Program Synthesis for Card GamesCode0
Combinational Q-Learning for Dou Di ZhuCode0
Application of Self-Play Reinforcement Learning to a Four-Player Game of Imperfect InformationCode0
Optimizing Hearthstone Agents using an Evolutionary AlgorithmCode0
Predicting Human Card Selection in Magic: The Gathering with Contextual Preference RankingCode0
Approximating Poker Probabilities with Deep LearningCode0
Q-DeckRec: A Fast Deck Recommendation System for Collectible Card GamesCode0
Enhancing Commentary Strategies for Imperfect Information Card Games: A Study of Large Language Models in Guandan CommentaryCode0
RLCard: A Toolkit for Reinforcement Learning in Card GamesCode0
Survey of Artificial Intelligence for Card Games and Its Application to the Swiss Game JassCode0
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
Two-Step Reinforcement Learning for Multistage Strategy Card Game—0
On the complexity of Dark Chinese Chess—0
A Taxonomy of Collectible Card Games from a Game-Playing AI Perspective—0
Cardiverse: Harnessing LLMs for Novel Card Game Prototyping—0
Contrastive Learning of Preferences with a Contextual InfoNCE Loss—0
DanZero: Mastering GuanDan Game with Reinforcement Learning—0
ELO System for Skat and Other Games of Chance—0
Evolutionary Approach to Collectible Card Game Arena Deckbuilding using Active Genes—0
Evolving Evaluation Functions for Collectible Card Game AI—0
GFlowVLM: Enhancing Multi-step Reasoning in Vision-Language Models with Generative Flow Networks—0
GTR: Guided Thought Reinforcement Prevents Thought Collapse in RL-based VLM Agent Training—0
History Filtering in Imperfect Information Games: Algorithms and Complexity—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
Neural Networks Models for Analyzing Magic: the Gathering Cards—0
Aggregated Semantic Matching for Short Text Entity Linking—0
Poker-CNN: A Pattern Learning Strategy for Making Draws and Bets in Poker Games—0
Policy Based Inference in Trick-Taking Card Games—0
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