pytorch-learn-reinforcement-learning
Super-mario-bros-PPO-pytorch
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| pytorch-learn-reinforcement-learning | Super-mario-bros-PPO-pytorch | |
|---|---|---|
| 3 | 1 | |
| 139 | 970 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 3 years ago | almost 3 years ago | |
| Python | Python | |
| MIT License | MIT License |
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pytorch-learn-reinforcement-learning
Super-mario-bros-PPO-pytorch
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[AI application] AI agent plays Contra
if you are interested in Super mario bros, here you are https://github.com/uvipen/Super-mario-bros-PPO-pytorch
What are some alternatives?
Tetris-deep-Q-learning-pytorch - Deep Q-learning for playing tetris game
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
tianshou - An elegant PyTorch deep reinforcement learning library.
muzero-general - MuZero
6DRepNet - Official Pytorch implementation of 6DRepNet: 6D Rotation representation for unconstrained head pose estimation.
stable-baselines - A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
Amortized-SVGD-GAN - Learning to draw samples: with application to amortized maximum likelihood estimator for generative adversarial learning
pytorch-a2c-ppo-acktr-gail - PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
nes-torch - Minimal PyTorch Library for Natural Evolution Strategies
pybullet-gym - Open-source implementations of OpenAI Gym MuJoCo environments for use with the OpenAI Gym Reinforcement Learning Research Platform.
pytorch-GAT - My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!
chess - Program for playing chess in the console against AI or human opponents