Drafting in Collectible Card Games via Reinforcement Learning

Collectible card games are played by tens of millions of players worldwide. Their intricate rules and diverse cards make them much harder than traditional card games... (read more)

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Datasets


  Add Datasets introduced or used in this paper
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
Card Games Legends of Code and Magic (Self-play) LSTM Win rate 61.495% # 2
Card Games Legends of Code and Magic (Self-play) History Win rate 56.635% # 3
Card Games Legends of Code and Magic (Self-play) Immediate Win rate 68.975% # 1

Methods used in the Paper


METHOD TYPE
Tanh Activation
Activation Functions
Sigmoid Activation
Activation Functions
LSTM
Recurrent Neural Networks
Entropy Regularization
Regularization
PPO
Policy Gradient Methods