mini-AlphaStar
pytorch-a2c-ppo-acktr-gail
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| mini-AlphaStar | pytorch-a2c-ppo-acktr-gail | |
|---|---|---|
| 1 | 3 | |
| 278 | 3,423 | |
| - | - | |
| 0.0 | 0.0 | |
| over 1 year ago | almost 2 years ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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mini-AlphaStar
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Better AI opponent
With quick googling I found this, but it seemed like there were no pretrained models and without a tech background this will be pretty much impossible to run.
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?
multi_agent_path_planning - Python implementation of a bunch of multi-robot path-planning algorithms.
soft-actor-critic - Implementation of the Soft Actor Critic algorithm using Pytorch.
DI-drive - Decision Intelligence Platform for Autonomous Driving simulation.
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
sharpy-sc2 - Python framework for rapid development of Starcraft 2 AI bots
dm_control - Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
minimalRL - Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
tensorforce - Tensorforce: a TensorFlow library for applied reinforcement learning
robo-vln - Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"
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