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Ppo Huggy

Developed by hellonihao
This is a PPO agent model trained using the Unity ML-Agents library, specifically designed to control the behavior of the virtual dog Huggy.
Downloads 52
Release Time : 2/18/2025

Model Overview

This model is trained using the PPO algorithm in deep reinforcement learning to control the virtual dog Huggy in completing specific tasks, such as interactive behaviors like fetching sticks.

Model Features

Based on Unity ML-Agents
Trained and deployed using the Unity ML-Agents library, compatible with Unity virtual environments.
PPO Algorithm
Utilizes the PPO algorithm in deep reinforcement learning to balance training stability and efficiency.
Interactive Demo
Supports viewing the agent's performance directly in a browser.

Model Capabilities

Virtual Character Control
Reinforcement Learning Decision-Making
Environment Interaction

Use Cases

Game AI
Virtual Pet Control
Control the virtual dog to complete interactive tasks like fetching sticks.
Observe the agent's learned behavior.
Educational Demo
Reinforcement Learning Teaching
Used to demonstrate the application of the PPO algorithm in virtual environments.
Visually showcases the reinforcement learning training process.
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