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Mlagents Pyramids
This is a reinforcement learning agent based on the PPO algorithm, trained in Unity's ML-Agents pyramid environment
Downloads 14
Release Time : 7/5/2022
Model Overview
This model is a deep reinforcement learning agent trained using the Unity ML-Agents framework, employing the PPO algorithm to learn navigation and task-solving capabilities in a pyramid environment
Model Features
Trained in Unity Environment
Trained in Unity's 3D pyramid environment, capable of handling complex 3D spatial navigation
PPO Algorithm Implementation
Utilizes Proximal Policy Optimization algorithm to balance exploration and exploitation for stable policy learning
Real-time Visualization
Supports real-time viewing of the agent's performance in a browser
Model Capabilities
3D Environment Navigation
Obstacle Avoidance
Goal-oriented Behavior
Reinforcement Learning Policy Optimization
Use Cases
Game AI
NPC Intelligent Navigation
Can be used for autonomous navigation of NPCs in complex 3D game environments
Robotics Control
Virtual Robot Training
Can serve as a virtual training environment for real robot control strategies
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