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Mlunitypyramids

Developed by motmono
This is a PPO agent model trained using the Unity ML-Agents library, specifically designed for gaming in pyramid environments.
Multimodal Fusion
TensorBoard
#Unity Game AI#Deep Reinforcement Learning#3D Environment Navigation
Downloads 21
Release Time : 10/31/2022

Model Overview

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

Model Features

Unity Environment Integration
Designed specifically for Unity ML-Agents pyramid environments, it can be seamlessly integrated into Unity game projects.
PPO Algorithm
Trained using the Proximal Policy Optimization algorithm, balancing exploration and exploitation.
Live Demo
Supports real-time gaming performance demonstrations via Hugging Face Spaces.

Model Capabilities

3D Environment Navigation
Game Objective Completion
Reinforcement Learning Decision Making

Use Cases

Game Development
AI Game Testing
Use this agent to automatically test game level designs.
Can evaluate level difficulty and balance.
Game NPC Behavior
Acts as an NPC behavior controller in pyramid environments.
Provides intelligent NPC behavior performance.
Educational Demonstration
Reinforcement Learning Teaching
Used to demonstrate the application of the PPO algorithm in 3D environments.
Visually showcases reinforcement learning effects.
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