Remtasya / Distributional-Multi-Agent-Actor-Critic-Reinforcement-Learning-MADDPG-Tennis-EnvironmentLinks
The state-of-the-art in multi-agent Reinforcement Learning is the MADDPG algorithm which utilises DDPG actor-critic neural networks where each agent uses centralized critic training but decentralized actor execution, and is capable of learning either cooperative or competitive environments. This is demonstrated on the Unity Tennis Environment.
☆29Updated 6 years ago
Alternatives and similar repositories for Distributional-Multi-Agent-Actor-Critic-Reinforcement-Learning-MADDPG-Tennis-Environment
Users that are interested in Distributional-Multi-Agent-Actor-Critic-Reinforcement-Learning-MADDPG-Tennis-Environment are comparing it to the libraries listed below
Sorting:
- Code for the RL method MATD3 described in the paper "Reducing Overestimation Bias in Multi-Agent Domains Using Double Centralized Critics…☆91Updated 5 years ago
- Code for our paper: Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation☆137Updated 5 months ago
- Deep recurrent Q learning on CartPole-v1 environment☆96Updated last year
- Implementations of MAPPO and IPPO on SMAC, the multi-agent StarCraft environment.☆75Updated 3 years ago
- demo of multi-agent reinforcement learning algorithms, such as ATT-MADDPG (Modelling the Dynamic Joint Policy of Teammates with Attention…☆64Updated 4 years ago
- MARLToolkit: The Multi-Agent Rainforcement Learning Toolkit. Include implementation of MAPPO, MADDPG, QMIX, VDN, COMA, IPPO, QTRAN, MAT..…☆151Updated last year
- Code for "ALMA: Hierarchical Learning for Composite Multi-Agent Tasks" NeurIPS 2022☆31Updated 3 years ago
- ICML 2019 RL for Real Life Workshop: Recurrent MADDPG for Partially Observable and Limited Communication Settings☆50Updated 5 years ago
- Multi-Agent Constrained Policy Optimisation (MACPO; MAPPO-L).☆208Updated last year
- Codes of GoMARL accompanying the paper "Automatic Grouping for Efficient Cooperative Multi-Agent Reinforcement Learning"(NeurIPS 2023). G…☆32Updated last year
- ☆106Updated 4 years ago
- PyTorch implementation of MATD3☆13Updated 5 years ago
- Jax and Torch Multi-Agent SAC on PettingZoo API☆97Updated last year
- The official code releasement of publications in MARL field of TJU RL lab.☆83Updated 3 years ago
- Multi-agent project (commnet, bicnet, maddpg) in pytorch for Multi-Agent Particle Environment☆116Updated 3 years ago
- Clean implementation of Multi-Agent Reinforcement Learning methods (MADDPG, MATD3, MASAC, MAD4PG) in TensorFlow 2.x☆164Updated 2 years ago
- implementation of MADDPG using PettingZoo and PyTorch☆161Updated 2 years ago
- UAV Logistics Environment for Multi-Agent Reinforcement Learning / Unity ML-Agents / Unity 3D☆107Updated last year
- Basic reinforcement learning algorithms. Including:DQN,Double DQN, Dueling DQN, SARSA, REINFORCE, baseline-REINFORCE, Actor-Critic,DDPG,D…☆96Updated 4 years ago
- Algorithm that combines QMIX with SAC for Multi-Agent Reinforcement Learning.☆56Updated 3 years ago
- Implementation of DyMA-CL, MARL algorithm☆28Updated 5 years ago
- Communication using GNN in MARL☆31Updated 3 years ago
- pytorch实现的一些MARL算法☆68Updated 4 years ago
- Public implementation of "Multi-Agent Graph-Attention Communication and Teaming" from AAMAS'21☆86Updated last year
- This repository is the official implementation of Learning Multi-Agent Coordination for Enhancing Target Coverage in Directional Sensor N…☆49Updated 5 years ago
- (ICML 2023) The official code for RACE: Improve Multi-Agent Reinforcement Learning with Representation Asymmetry and Collaborative Evolut…☆41Updated 2 years ago
- This is the official implementation of Multi-Agent PPO.☆128Updated 2 years ago
- Implementation of centralized training, centralized execution of Soft Actor-Critic (SAC) on a Tennis multiagent Unity environment.☆40Updated 4 years ago
- a clean and robust Pytorch implementation of SAC on continuous action space☆90Updated 8 months ago
- Codes for the paper "Consensus Learning for Cooperative Multi-Agent Reinforcement Learning"☆17Updated 3 years ago