TestPyramidsRND Open-source Reinforcement Learning Agent Model - Free Deployment for Pyramid Environment Training

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Testpyramidsrnd

Developed by michael20at

This is a reinforcement learning agent model trained using the PPO algorithm in the Unity ML-Agents pyramid environment

Object Detection

TensorBoard

#Unity3D Reinforcement Learning #PPO Algorithm Implementation #3D Environment Navigation

Downloads 69

Release Time : 9/20/2022

Model Overview

This model is based on the PPO (Proximal Policy Optimization) algorithm and trained in the Unity ML-Agents pyramid environment, capable of completing specific 3D environment navigation tasks.

Model Features

Based on PPO Algorithm

Trained using the Proximal Policy Optimization algorithm, a stable reinforcement learning algorithm

Unity Environment Integration

Specifically trained for the Unity ML-Agents pyramid environment and can be seamlessly integrated into Unity projects

3D Navigation Capability

Capable of navigating and completing tasks in complex 3D environments

Model Capabilities

3D Environment Navigation

Reinforcement Learning Decision Making

Unity Environment Interaction

Use Cases

Game AI

Intelligent NPC Navigation

Provides intelligent navigation capabilities for NPCs in game environments

NPCs can autonomously move in complex 3D environments

Robot Simulation

Virtual Robot Training

Used to train virtual robots' mobility in complex environments

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Testpyramidsrnd

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 PPO Agent Playing Pyramids

🚀 Quick Start

✨ Features

📦 Installation

💻 Usage Examples

Basic Usage

Resume the training

Watch your Agent play