Free and open-source testpyramidsrnd reinforcement learning agent - Can be used for training in the Unity ML-Agents pyramid environment

Testpyramidsrnd

Developed by mariastull

This is a reinforcement learning agent based on the PPO algorithm, specifically trained for the Unity ML-Agents pyramid environment.

Object Detection

TensorBoard

#Unity Reinforcement Learning #3D Environment Navigation #PPO Algorithm

Downloads 22

Release Time : 7/11/2022

Model Overview

This model is trained using the PPO (Proximal Policy Optimization) algorithm and can perform navigation or goal achievement tasks in Unity's ML-Agents pyramid environment.

Model Features

Unity Environment Integration

Designed specifically for the Unity ML-Agents pyramid environment, it can run directly in the Unity simulator.

PPO Algorithm

Uses the Proximal Policy Optimization algorithm to balance exploration and exploitation for stable training.

Visual Demonstration

Supports direct viewing of the agent's performance via Hugging Face Spaces.

Model Capabilities

3D Environment Navigation

Target Recognition and Achievement

Reinforcement Learning Decision Making

Use Cases

Game AI

Pyramid Exploration AI

The agent autonomously explores and completes tasks in the pyramid environment.

Observe the agent's decision-making process in a complex 3D environment.

Reinforcement Learning Education

PPO Algorithm Demonstration

Demonstrates the practical application of the PPO algorithm in a 3D environment.

Intuitively understand the reinforcement learning training process.

Featured Recommended AI Models

Empowering the Future, Your AI Solution Knowledge Base

English 简体中文繁體中文にほんご

Testpyramidsrnd

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 PPO Agent Playing Pyramids

🚀 Quick Start

📚 Documentation

💻 Usage Examples

Basic Usage

Resume the training

Watch your Agent play