tf2multiagentrl
DeepRL-TensorFlow2
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| tf2multiagentrl | DeepRL-TensorFlow2 | |
|---|---|---|
| - | 2 | |
| 110 | 573 | |
| - | - | |
| 3.4 | 0.0 | |
| 6 months ago | almost 2 years ago | |
| Python | Python | |
| - | Apache License 2.0 |
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tf2multiagentrl
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Tracking mentions began in Dec 2020.
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?
Mava - 🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX
soft-actor-critic - Re-implementation of Soft-Actor-Critic (SAC) in TensorFlow 2.0
rlalgorithms-tf2 - Packaged deep reinforcement learning algorithms in tensorflow 2.x
TensorFlow2.0-for-Deep-Reinforcement-Learning - TensorFlow 2.0 for Deep Reinforcement Learning. :octopus:
ai-economist - Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).
tensorforce - Tensorforce: a TensorFlow library for applied reinforcement learning
ydata-synthetic - Synthetic data generators for tabular and time-series data
minimalRL - Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
machin - Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
Reinforcement-Learning - Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
Fleet-AI - Using Reinforcement Learning to play Battleship
pomdp-baselines - Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022