Benchmark present methods for efficient reinforcement learning. Methods include Reptile, MAML, Residual Policy, etc. RL algorithms include DDPG, PPO.
APACHE-2.0 License
A comparison of parameter space noise methods for exploration in deep reinforcement learning
Implementations of Reinforcement Learning and Planning algorithms
The next generation deep reinforcement learning tookit
Examples of published reinforcement learning algorithms in recent literature implemented in Tenso...
rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compa...
Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning
RLToolkit is a flexible and high-efficient reinforcement learning framework. Include implementati...
A PyTorch reinforcement learning library for generalizable and reproducible algorithm implementat...
Minimal and Clean Reinforcement Learning Examples
PFRL: a PyTorch-based deep reinforcement learning library
PyTorch implementations of deep reinforcement learning algorithms and environments
Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcem...
Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
PyTorch based Reinforcement Learning for OpenSim Prosthetics and Learning to Run environments