AIbase
EN
Home
Mlagents Pyramids
M

Mlagents Pyramids

Developed by Forkits
This is a reinforcement learning model based on the PPO algorithm, trained in the pyramid environment using Unity ML-Agents
Molecular Model
TensorBoard
#Unity Reinforcement Learning#Pyramid Environment Navigation#PPO Algorithm
Downloads 19
Release Time : 6/25/2022

Model Overview

This model is a deep reinforcement learning agent specifically trained for Unity's Pyramids environment, using the PPO algorithm to learn navigation and task completion in 3D environments

Model Features

Unity Environment Integration
Designed for Unity 3D environments, can run directly in Unity simulators
PPO Algorithm Implementation
Uses Proximal Policy Optimization algorithm for stable and efficient reinforcement learning training
3D Navigation Capability
Capable of autonomous navigation and task completion in complex 3D pyramid environments

Model Capabilities

3D Environment Navigation
Reinforcement Learning Decision Making
Unity Environment Interaction

Use Cases

Game AI
Autonomous Navigation NPC
Can serve as non-player characters in games, moving autonomously in complex 3D environments
Achieves intelligent path planning and environmental interaction
Robot Simulation
Virtual Robot Training
Used to train virtual robots' mobility in complex environments
Provides simulation training foundation for real robot control
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
EnglishįŽ€äŊ“中文įšéĢ”中文ãĢãģんご
Š 2025AIbase