This is the Linux app named MADDPG whose latest release can be downloaded as maddpgsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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MADDPG
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DESCRIPTION
MADDPG (Multi-Agent Deep Deterministic Policy Gradient) is the official code release from OpenAI’s paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The repository implements a multi-agent reinforcement learning algorithm that extends DDPG to scenarios where multiple agents interact in shared environments. Each agent has its own policy, but training uses centralized critics conditioned on the observations and actions of all agents, enabling learning in cooperative, competitive, and mixed settings. The code is built on top of TensorFlow and integrates with the Multiagent Particle Environments (MPE) for benchmarking. Researchers can use it to reproduce the experiments presented in the paper, which demonstrate how agents learn behaviors such as coordination, competition, and communication. Although archived, MADDPG remains a widely cited baseline in multi-agent reinforcement learning research and has inspired further algorithmic developments.
Features
- Implementation of Multi-Agent DDPG with centralized critics
- Supports cooperative, competitive, and mixed-agent settings
- TensorFlow-based training pipeline for multi-agent RL
- Compatible with Multiagent Particle Environments (MPE)
- Scripts for reproducing results from the original paper
- Reference implementation for research in multi-agent RL
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/maddpg.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
