GitHub / Pabloo22 / tabular_rl
A simple Reinforcement Learning framework to decouple agents from environments in discrete-state settings with implementations of double Q-learning and policy iteration through dynamic programming.
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PURL: pkg:github/Pabloo22/tabular_rl
Stars: 6
Forks: 0
Open issues: 0
License: mit
Language: Python
Size: 248 KB
Dependencies parsed at: Pending
Created at: over 2 years ago
Updated at: 6 months ago
Pushed at: 7 months ago
Last synced at: 3 days ago
Commit Stats
Commits: 78
Authors: 3
Mean commits per author: 26.0
Development Distribution Score: 0.064
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/Pabloo22/tabular_rl
Topics: dynamic-programming, library, q-learning, reinforcement-learning, reinforcement-learning-agent, reinforcement-learning-environments