Machin
A PyTorch reinforcement learning library implementing DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, and IMPALA.
What is Machin?
Machin is a reinforcement learning library designed for PyTorch that implements a wide range of modern RL algorithms including DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, and IMPALA. It provides a simple and clear implementation of these algorithms to solve complex decision-making problems in custom environments.
Researchers and developers working on reinforcement learning projects who prefer PyTorch and need a library with readable, reusable implementations of advanced RL algorithms.
Developers choose Machin for its minimal abstractions, detailed documentation, and straightforward approach similar to PyTorch, making it easier to adapt algorithms to custom environments compared to more complex frameworks.
Overview
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
Use Cases
Best For
- Implementing single-agent RL algorithms like DQN or PPO in PyTorch
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