rlalgorithms-tf2 VS tf2multiagentrl

Compare rlalgorithms-tf2 vs tf2multiagentrl and see what are their differences.

tf2multiagentrl

Clean implementation of Multi-Agent Reinforcement Learning methods (MADDPG, MATD3, MASAC, MAD4PG) in TensorFlow 2.x (by JohannesAck)
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rlalgorithms-tf2 tf2multiagentrl
18 -
45 111
- -
4.7 3.4
almost 2 years ago 7 months ago
Python Python
MIT License -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

rlalgorithms-tf2

Posts with mentions or reviews of rlalgorithms-tf2. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-06.

tf2multiagentrl

Posts with mentions or reviews of tf2multiagentrl. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning tf2multiagentrl yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing rlalgorithms-tf2 and tf2multiagentrl you can also consider the following projects:

stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

DeepRL-TensorFlow2 - 🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2

IRL - Algorithms for Inverse Reinforcement Learning

Mava - 🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX

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).

TensorLayer - Deep Learning and Reinforcement Learning Library for Scientists and Engineers

DRL-robot-navigation - Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles.

agents - TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.

loneliless - A Deep-Q Network playing a single player Pong game. Network done in Python (Tensorflow-gpu) with the single player Pong game implemented in C++ (Openframeworks) and both binded with Pybind11.

rlqp - Accelerating Quadratic Optimization with Reinforcement Learning