Multi-Objective Reinforcement Learning algorithms implementations.
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Updated
May 29, 2024 - Python
Multi-Objective Reinforcement Learning algorithms implementations.
Reinforcement Learning environments for Traffic Signal Control with SUMO. Compatible with Gymnasium, PettingZoo, and popular RL libraries.
TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
RL-Toolkit: A Research Framework for Robotics
Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.
Repo for the Deep Reinforcement Learning Nanodegree program
Custom Reinforcement Learning Agents
A collection of RL algorithms written in PyTorch
Short own implementation of the game snake. In this project I'am using the ray library together with ray tune and a custom PPO model.
Code for "Constrained Variational Policy Optimization for Safe Reinforcement Learning" (ICML 2022)
Using reinforcement learning to play games.
A toolkit for reproducible reinforcement learning research.
Our VMAgent is a platform for exploiting Reinforcement Learning (RL) on Virtual Machine (VM) scheduling tasks.
Tensorflow 2 Reinforcement Learning Cookbook, published by Packt
Optimized version of the MinAtar (testbed for AI agents) codebase along with benchmarks for standard Reinforcement Learning agents on various environments.
Tic-tac-toe/"noughts & crosses" written in Clojure (CLI + deps). AI powered by Monte Carlo tree search algorithm
Tasks with combinatorial structure embedded in MuJoCo robotics environments.
Pytorch Implementation of Reinforcement Learning Algorithms ( Soft Actor Critic(SAC)/ DDPG / TD3 /DQN / A2C/ PPO / TRPO)
reinforcement learning DQN method to solve OpenAi Gym "LunarLander-v2" by usnig a Deep Neuralnetwork
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