rlcard vs on-policy
rlcard: RLCard is a toolkit designed for Reinforcement Learning in card games, providing multiple card environments with easy-to-use interfaces. Its goal is to bridge reinforcement learning and imperfect information games, supporting various RL and searching algorithms.; on-policy: This repository implements MAPPO, a multi-agent variant of PPO, widely used in cooperative multi-agent games and research. It provides robust implementations for various multi-agent environments like StarCraft II, Hanabi, and Google Research Football, along with detailed training scripts and hyperparameter guidance.
TL;DR
Developing and testing reinforcement learning agents for various card games.
Research and experimentation in cooperative multi-agent reinforcement learning
Side-by-Side Comparison
rlcardon-policyFeatures
rlcardon-policyUse Cases
rlcardon-policyFAQ
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