fetch-and-slide-HRE-PRE
pytorch-a2c-ppo-acktr-gail
| fetch-and-slide-HRE-PRE | pytorch-a2c-ppo-acktr-gail | |
|---|---|---|
| 1 | 3 | |
| 3 | 3,423 | |
| - | - | |
| 0.0 | 0.0 | |
| about 2 years ago | almost 2 years ago | |
| Python | Python | |
| - | MIT License |
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fetch-and-slide-HRE-PRE
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Installing & Using MuJoCo 2.1.5 with OpenAi Gym
I had setup difficulties working with mujoco on m1 mac. I had to setup symlinks and also set cxx ans LDFLAGS in order to run mujoco properly. You can check the install script here: https://github.com/DeconvFFT/fetch-and-slide-HRE-PRE
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).
What are some alternatives?
dm_control - Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
soft-actor-critic - Implementation of the Soft Actor Critic algorithm using Pytorch.
turtlebot3_ddpg_collision_avoidance - Mapless Collision Avoidance of Turtlebot3 Mobile Robot Using DDPG and Prioritized Experience Replay
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
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]