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Testpyramidsrnd

Developed by bothrajat
This is a PPO agent model trained in the Pyramids environment using the Unity ML-Agents library, capable of performing in-game tasks within this environment.
Object Detection
TensorBoard
#Unity Reinforcement Learning#3D Environment Navigation#PPO Algorithm
Downloads 21
Release Time : 7/13/2022

Model Overview

This model is a deep reinforcement learning agent trained with the PPO algorithm in Unity's Pyramids environment, designed to solve specific game tasks.

Model Features

Based on PPO Algorithm
Trained using the Proximal Policy Optimization algorithm, a stable reinforcement learning method.
Unity ML-Agents Integration
Fully compatible with the Unity ML-Agents library, easily deployable in Unity environments.
Specialized for Pyramids Environment
Specifically trained for the Pyramids game environment, effectively solving its unique tasks.

Model Capabilities

Game decision-making in the Pyramids environment
Execution of reinforcement learning strategies
Real-time environment interaction

Use Cases

Game AI
Pyramids Game AI
Acts as an intelligent agent in the Pyramids game, autonomously completing game tasks
Reinforcement Learning Research
PPO Algorithm Validation
Used to validate the performance of the PPO algorithm in specific environments
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