pytorch-a2c-ppo-acktr jperl · COMPLETED
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO) and Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR).
github.com/jperl/pytorch-a2c-ppo-acktr · ★ 0 · Forks 0 · Size 204 KB
SUMMARY
Technologies 3
Scored 3
Observed 3
Practices 6
Evidence 3
Skips 0
COVERAGE
Analyzed 23 files · 28 commits · 0 API calls
TECHNOLOGIES & DEPTH
Markdown LANGUAGE Depth 70
1 files · PRODUCTION
Python LANGUAGE Depth 70
9 files · PRODUCTION
NumPy LIBRARY Depth 58
2 files · PRODUCTION
PRACTICES
documentation · observedautomated_tests · absentcontinuous_integration · absentcontainerization · absentlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2017-09-07
Last commit 2017-10-07
Active months 2
Commits 28