The Multi-Agent DDPG repository provides a PyTorch-based implementation of Deep Deterministic Policy Gradient for multiple agents in Unity environments. It integrates seamlessly with Unity ML-Agents, supports customizable hyperparameters, logging, and TensorBoard visualization. Researchers and developers can quickly adapt the code to different cooperative behaviors, reward structures, and environments to conduct experiments or prototypes with minimal setup.
AI Platforms & Frameworks
#multi-agent RL
#reinforcement learning
#PyTorch framework
#Unity ML-Agents
#decentralized DDPG
#environment wrapping
#TensorBoard visualization
#custom reward functions
#parallel training
#collaborative navigation
#agent policies
#ML experimentation
#open-source project
#simulated environments
#training scripts
#AI Agents
#modular codebase
#hyperparameter tuning
#real-time monitoring
#benchmarking AI
...
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Multi-Agent DDPG with PyTorch & Unity ML-Agents
The Multi-Agent DDPG repository provides a PyTorch-based implementation of Deep Deterministic Policy Gradient for multiple agents in Unity environments. It integrates seamlessly with Unity ML-Agents, supports customizable hyperparameters, logging, and TensorBoard visualization. Researchers and developers can quickly adapt the code to different cooperative behaviors, reward structures, and environments to conduct experiments or prototypes with minimal setup.
AI Platforms & Frameworks
#multi-agent RL
#reinforcement learning
#PyTorch framework
#Unity ML-Agents
#decentralized DDPG
#environment wrapping
#TensorBoard visualization
#custom reward functions
#parallel training
#collaborative navigation
#agent policies
#ML experimentation
#open-source project
#simulated environments
#training scripts
#AI Agents
#modular codebase
#hyperparameter tuning
#real-time monitoring
#benchmarking AI
...
Featured
What is Multi-Agent DDPG with PyTorch & Unity ML-Agents?
This open-source project delivers a complete multi-agent reinforcement learning framework built on PyTorch and Unity ML-Agents. It offers decentralized DDPG algorithms, environment wrappers, and training scripts. Users can configure agent policies, critic networks, replay buffers, and parallel training workers. Logging hooks allow TensorBoard monitoring, while modular code supports custom reward functions and environment parameters. The repository includes sample Unity scenes demonstrating collaborative navigation tasks, making it ideal for extending and benchmarking multi-agent scenarios in simulation.
Who will use Multi-Agent DDPG with PyTorch & Unity ML-Agents?
- Reinforcement learning researchers
- Game developers
- ML engineers
- AI students and educators
How to use the Multi-Agent DDPG with PyTorch & Unity ML-Agents?
- Step1: Clone the GitHub repository to your local machine.
- Step2: Install dependencies: Python, PyTorch, Unity ML-Agents package.
- Step3: Open the Unity sample scene and configure agent settings.
- Step4: Adjust hyperparameters in the training script as needed.
- Step5: Run the training script to start learning and monitor progress in TensorBoard.
- Step6: Analyze saved models and visualize agent behaviors within Unity.
Platform
- mac
- windows
- linux
Multi-Agent DDPG with PyTorch & Unity ML-Agents's Core Features & Benefits
The Core Features
- Decentralized multi-agent DDPG implementation
- Integration with Unity ML-Agents
- Customizable hyperparameters and reward functions
- TensorBoard logging and visualization
- Sample Unity scenes for collaborative tasks
The Benefits
- Accelerates multi-agent RL experiments
- Reusable and modular codebase
- Easy integration with Unity environments
- Scalable training with parallel workers
- Supports real-time visualization of agent behaviors
Multi-Agent DDPG with PyTorch & Unity ML-Agents's Main Use Cases & Applications
- Training cooperative robot navigation in simulation
- Developing multi-character game AI behaviors
- Academic research in multi-agent reinforcement learning
- Benchmarking decentralized policies
- Prototyping collaborative agent scenarios
FAQs of Multi-Agent DDPG with PyTorch & Unity ML-Agents
Multi-Agent DDPG with PyTorch & Unity ML-Agents Company Information
Multi-Agent DDPG with PyTorch & Unity ML-Agents Reviews
5/5
Multi-Agent DDPG with PyTorch & Unity ML-Agents's Main Competitors and alternatives?
- OpenAI Baselines
- RLlib
- Stable Baselines3
- Unity ML-Agents Official Examples
- PettingZoo
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