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Mlagents PushBlock
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Mlagents PushBlock

Developed by infinitejoy
This is a PPO agent trained using Unity ML-Agents, specifically designed to solve the PushBlock game task.
Protein Model
TensorBoard
#Unity Reinforcement Learning#Sokoban Game AI#PPO Algorithm
Downloads 24
Release Time : 7/11/2022

Model Overview

This model is a deep reinforcement learning agent based on the PPO algorithm, trained to effectively push blocks and complete tasks in Unity's PushBlock environment.

Model Features

Based on Unity ML-Agents
Trained using Unity's ML-Agents framework, enabling seamless integration with Unity environments
PPO Algorithm Implementation
Utilizes the Proximal Policy Optimization algorithm to balance exploration and exploitation
Game Task Solving
Specifically trained for the PushBlock game environment, capable of effectively completing block-pushing tasks

Model Capabilities

Game Strategy Learning
Environment Interaction
Task Solving

Use Cases

Game AI
PushBlock Game AI
Acts as an intelligent opponent or assistant in the PushBlock game
Capable of effectively completing block-pushing tasks
Reinforcement Learning Research
PPO Algorithm Demonstration
Demonstrates the application of the PPO algorithm in a simple 3D environment
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