minimalRL
DeepRL-TensorFlow2
| minimalRL | DeepRL-TensorFlow2 | |
|---|---|---|
| 5 | 2 | |
| 2,725 | 573 | |
| - | - | |
| 1.6 | 0.0 | |
| about 1 year ago | almost 2 years ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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minimalRL
- Does anyone know good python sources hardcoded of RL?
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Question about pseudocodes
Did you try minimalRL?
- Rl algorithm implemented
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RL agent for simple games?
This github is great.
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PPO+LSTM Implementation
Maybe this implementation helps: https://github.com/seungeunrho/minimalRL/blob/master/ppo-lstm.py
DeepRL-TensorFlow2
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PPO implementation in TensorFlow2
I've been searching for a clean, good, and understandable implementation of PPO for continuous action space with TF2 witch is understandable enough for me to apply my modifications, but the closest thing that I have found is this code which seems to not work properly even on a simple gym cartpole env (discussed issues in git-hub repo suggest the same problem) so I have some doubts :). I was wondering whether you could recommend an implementation that you trust and suggest :)
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Question about using tf.stop_gradient in separate Actor-Critic networks for A2C implementation for TF2
I have been looking at this implementation of A2C. Here the author of the code uses stop_gradient only on the critic network at L90 bur not in the actor network L61 for the continuous case. However , it is used both in actor and critic networks for the discrete case. Can someone explain me why?
What are some alternatives?
ElegantRL - Massively Parallel Deep Reinforcement Learning. 🔥
soft-actor-critic - Re-implementation of Soft-Actor-Critic (SAC) in TensorFlow 2.0
Pytorch-PCGrad - Pytorch reimplementation for "Gradient Surgery for Multi-Task Learning"
tensorforce - Tensorforce: a TensorFlow library for applied reinforcement learning
rlpyt - Reinforcement Learning in PyTorch
TensorFlow2.0-for-Deep-Reinforcement-Learning - TensorFlow 2.0 for Deep Reinforcement Learning. :octopus:
pomdp-baselines - Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022
ydata-synthetic - Synthetic data generators for tabular and time-series data
deep-RL-trading - playing idealized trading games with deep reinforcement learning
machin - Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
ultimate-volleyball - 3D RL Volleyball environment built on Unity ML-Agents
tf2multiagentrl - Clean implementation of Multi-Agent Reinforcement Learning methods (MADDPG, MATD3, MASAC, MAD4PG) in TensorFlow 2.x