ML - agents_pyramids Open - source Reinforcement Learning Agents - Free Support for Task Navigation in Unity Pyramid Environment

ML Agents Pyramids

Developed by rram12

This is a reinforcement learning agent based on the PPO algorithm, specifically trained to navigate and complete tasks in Unity's ML-Agents pyramids environment.

Object Detection

TensorBoard

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

Downloads 25

Release Time : 9/22/2022

Model Overview

This model is trained using the PPO (Proximal Policy Optimization) algorithm in Unity ML-Agents' pyramids environment, capable of learning to navigate and solve tasks in complex 3D environments.

Model Features

Based on PPO Algorithm

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

Unity Environment Integration

Designed specifically for Unity ML-Agents' pyramids 3D environment

End-to-End Learning

Learns navigation policies directly from sensor inputs without manually designed features

Model Capabilities

3D Environment Navigation

Obstacle Avoidance

Goal-Oriented Behavior

Reinforcement Learning Policy Execution

Use Cases

Game AI

Smart NPC Navigation

Provides intelligent navigation capabilities for NPC characters in 3D game environments

NPCs can autonomously move and complete tasks in complex environments

Robot Simulation

Robot Path Planning

Provides navigation capabilities for simulated robots in complex environments

Robots can learn effective path planning strategies

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ML Agents Pyramids

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 PPO Agent Playing Pyramids

🚀 Quick Start

💻 Usage Examples

Basic Usage

Resume the training

Watch your Agent play