Testpyramidsrnd Open-Source Reinforcement Learning Agent - Efficiently Perform Tasks in Unity Pyramid Environment

Testpyramidsrnd

Developed by reachrkr

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

Multimodal Fusion

TensorBoard

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

Downloads 59

Release Time : 7/28/2022

Model Overview

This model uses the PPO (Proximal Policy Optimization) algorithm for training in Unity's ML-Agents pyramid environment, capable of completing specific navigation or task-solving in this 3D environment.

Model Features

Unity Environment Integration

Designed specifically for the Unity ML-Agents pyramid environment, seamlessly integrates with Unity3D.

PPO Algorithm Implementation

Utilizes the Proximal Policy Optimization algorithm to balance exploration and exploitation.

3D Navigation Capability

Capable of effective navigation in complex 3D pyramid environments.

Model Capabilities

3D Environment Navigation

Reinforcement Learning Decision Making

Unity Environment Interaction

Use Cases

Game AI

Smart NPC Control

Controls NPCs in game environments to complete specific tasks.

NPCs can autonomously navigate and complete tasks.

Robot Simulation

Virtual Robot Training

Trains robot navigation capabilities in virtual environments.

Provides pre-trained models for real-world robot deployment.

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Testpyramidsrnd

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 PPO Agent Playing Pyramids

🚀 Quick Start

Usage (with ML - Agents)

Resume the training

Watch your Agent play