policy
Recursive-Learning-Chess
alcsel · JAX
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Overview
Name
Recursive-Learning-Chess
Author
alcsel
Framework
JAX
License
unknown
Skill type
other
Evidence level
untested
Task description
Chess RL agent trained via self-play using JAX/Flax on PGX environment. Features 8 residual blocks, actor-critic architecture, and epsilon-greedy exploration with a frozen opponent updated every 500 batches. Trained on Kaggle T4 with 2048 parallel environments.
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
3+17 mentioned but not in catalog yetCompatible environments
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Datasets that reference this policy
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