DeepRL-TensorFlow2 VS minimalRL

Compare DeepRL-TensorFlow2 vs minimalRL and see what are their differences.

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DeepRL-TensorFlow2 minimalRL
2 5
573 2,725
- -
0.0 1.6
almost 2 years ago about 1 year ago
Python Python
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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DeepRL-TensorFlow2

Posts with mentions or reviews of DeepRL-TensorFlow2. We have used some of these posts to build our list of alternatives and similar projects.
  • PPO implementation in TensorFlow2
    1 project | /r/reinforcementlearning | 12 Sep 2021
    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 :)
  • Question about using tf.stop_gradient in separate Actor-Critic networks for A2C implementation for TF2
    1 project | /r/reinforcementlearning | 24 Mar 2021
    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?

minimalRL

Posts with mentions or reviews of minimalRL. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-07-18.

What are some alternatives?

When comparing DeepRL-TensorFlow2 and minimalRL you can also consider the following projects:

soft-actor-critic - Re-implementation of Soft-Actor-Critic (SAC) in TensorFlow 2.0

ElegantRL - Massively Parallel Deep Reinforcement Learning. 🔥

tensorforce - Tensorforce: a TensorFlow library for applied reinforcement learning

Pytorch-PCGrad - Pytorch reimplementation for "Gradient Surgery for Multi-Task Learning"

TensorFlow2.0-for-Deep-Reinforcement-Learning - TensorFlow 2.0 for Deep Reinforcement Learning. :octopus:

rlpyt - Reinforcement Learning in PyTorch

ydata-synthetic - Synthetic data generators for tabular and time-series data

pomdp-baselines - Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022

machin - Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...

deep-RL-trading - playing idealized trading games with deep reinforcement learning

tf2multiagentrl - Clean implementation of Multi-Agent Reinforcement Learning methods (MADDPG, MATD3, MASAC, MAD4PG) in TensorFlow 2.x

ultimate-volleyball - 3D RL Volleyball environment built on Unity ML-Agents