Repository profile
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
Repository updates
Get generated iffiX/machin development summaries by email, or follow the weekly and monthly RSS feeds.
Sign in to subscribe by email. RSS feeds are public.
Sign in to subscribeTracked growth, recent movement, and commit velocity from stored repository snapshots.
Latest capture 2026-07-07 03:15
6 captures since 2026-05-22
Stars from baseline -1
All tracked data
Frameworks, package managers, ecosystems, and dependency manifests found during catalog scans.
Scanned 2026-07-07 03:15
setup.py
python ecosystem,
13 dependencies
docs/requirements.txt
python ecosystem,
15 dependencies
test_lib/multiagent-particle-envs/setup.py
python ecosystem,
2 dependencies
Searchable topics, generated tags, and stack labels that explain where this repository fits.
Agent instructions and tool configuration paths found in the repository tree.
Nearest indexed repositories by embedding similarity.
Clean PyTorch implementations of imitation and reward learning algorithms
OpenMMLab Foundational Library for Training Deep Learning Models
Implementation of all RL algorithms in a simpler way
Reinforcement Learning in PyTorch
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
