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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
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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