Card Games
18 papers with code • 0 benchmarks • 1 datasets
Card games involve playing cards: the task is to train an agent to play the game with specified rules and beat other players.
Benchmarks
These leaderboards are used to track progress in Card Games
Cards Against Humanity
Most implemented papers
RLCard: A Toolkit for Reinforcement Learning in Card Games
datamllab/rlcard
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The goal of RLCard is to bridge reinforcement learning and imperfect information games, and push forward the research of reinforcement learning in domains with multiple agents, large state and action space, and sparse reward.
Deep Reinforcement Learning from Self-Play in Imperfect-Information Games
When applied to Leduc poker, Neural Fictitious Self-Play (NFSP) approached a Nash equilibrium, whereas common reinforcement learning methods diverged.
Latent Predictor Networks for Code Generation
Many language generation tasks require the production of text conditioned on both structured and unstructured inputs.
Application of Self-Play Reinforcement Learning to a Four-Player Game of Imperfect Information
henrycharlesworth/big2_PPOalgorithm
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We introduce a new virtual environment for simulating a card game known as "Big 2".
Survey of Artificial Intelligence for Card Games and Its Application to the Swiss Game Jass
Jass is a very popular card game in Switzerland and is closely connected with Swiss culture.
Q-DeckRec: A Fast Deck Recommendation System for Collectible Card Games
czxttkl/X-AI
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Deck building is a crucial component in playing Collectible Card Games (CCGs).
Approximating Poker Probabilities with Deep Learning
brandinho/Poker-Probability-Approximation
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Many poker systems, whether created with heuristics or machine learning, rely on the probability of winning as a key input.
Combinational Q-Learning for Dou Di Zhu
Deep reinforcement learning (DRL) has gained a lot of attention in recent years, and has been proven to be able to play Atari games and Go at or above human levels.
The Winnability of Klondike Solitaire and Many Other Patience Games
Our ignorance of the winnability percentage of the game in the Windows Solitaire program, more properly called 'Klondike', has been described as "one of the embarrassments of applied mathematics".
Drafting in Collectible Card Games via Reinforcement Learning
In this paper, we present a deep reinforcement learning approach for deck building in arena mode - an understudied game mode present in many collectible card games.
