pytorch-a2c-ppo-acktr-gail
soft-actor-critic
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| pytorch-a2c-ppo-acktr-gail | soft-actor-critic | |
|---|---|---|
| 3 | 1 | |
| 3,423 | 6 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 2 years ago | almost 3 years ago | |
| Python | Python | |
| MIT License | MIT License |
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pytorch-a2c-ppo-acktr-gail
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How does advantage estimation is done when episodes are of variable length in PPO?
As an example look at "compute_returns" function here (and pay attention to how self.masks is used): https://github.com/ikostrikov/pytorch-a2c-ppo-acktr-gail/blob/master/a2c_ppo_acktr/storage.py
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How to pretrain a model on expert data?
Try using an imitation learning algorithm. Two popular options are MaxEnt IRL and GAIL. This repository has GAIL implementation and this repository has MaxEnt IRL and GAIL implementation. There are other implementations too that you can check out.
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Trying to Train PPO Agent for Pendulum-v0 from Pixel Inputs
For the PPO, I used this repo, which includes most tricks including GAE, normalized rewards, etc. I have verified this repo works for the traditional Pendulum-v0 task and Atari games (Pong and Breakout).
soft-actor-critic
What are some alternatives?
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
stable-baselines - A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
dm_control - Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
tensorforce - Tensorforce: a TensorFlow library for applied reinforcement learning
TensorFlow2.0-for-Deep-Reinforcement-Learning - TensorFlow 2.0 for Deep Reinforcement Learning. :octopus:
PCGrad - Code for "Gradient Surgery for Multi-Task Learning"
DI-engine - OpenDILab Decision AI Engine
Reinforcement-Learning - Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
pomdp-baselines - Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022
metaworld - Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning [Moved to: https://github.com/Farama-Foundation/Metaworld]
seed_rl - SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.
autonomous-learning-library - A PyTorch library for building deep reinforcement learning agents.