AIbase
EN
Home
Pyramidsrnd
P

Pyramidsrnd

Developed by mrm8488
This is a PPO agent model trained using the Unity ML-Agents library, specifically designed for gaming and decision-making in the pyramid environment.
Object Detection
TensorBoard
#Unity Game AI#Deep Reinforcement Learning#PPO Algorithm
Downloads 25
Release Time : 8/1/2022

Model Overview

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

Model Features

Based on PPO Algorithm
Trained using the Proximal Policy Optimization algorithm, an advanced reinforcement learning algorithm.
Unity Environment Integration
Designed specifically for the Unity ML-Agents pyramid environment, seamlessly integrating with the Unity game engine.
Resumable Training
Supports resuming the training process via command-line parameters, facilitating continued optimization of model performance.

Model Capabilities

Environment Perception
Game Decision-Making
Path Planning
Goal-Oriented Behavior

Use Cases

Game AI
Pyramid Environment Navigation
The agent navigates and completes tasks in the pyramid environment.
Observe the agent's decision paths and efficiency in the environment.
Reinforcement Learning Teaching
Serves as a teaching example for reinforcement learning algorithms.
Demonstrates the application effects of the PPO algorithm in a real environment.
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
English简体中文繁體中文にほんご
© 2025AIbase