Play a snowball throwing game
Play a JavaScript-based adventure game
Run and customize ML agents in a simulation
Play Gomoku against an AI
Control a vehicle with WASD to simulate real physics
Play a Unity-based block pushing game
Create and compete with AI agents in a "Who's Spy" game
Play Connect-4 against an AI opponent
Play the Space Escape game
Play a narrative-driven game enhanced by AI
Explore a pyramid-solving game with AI
Control a vehicle with WASD keys in a physics simulation
Play web-based vehicle physics simulations using WASD controls
ML Agents SnowballTarget is a Unity package designed for creating AI-powered snowball throwing games. It leverages Unity's ML-Agents toolkit to enable AI agents to learn and play a snowball-throwing game. The package provides a pre-built environment and assets for developers to integrate AI into their snowball-themed games.
• AI-Powered Snowball Throwing: The AI agent can autonomously throw snowballs at targets using machine learning algorithms. • Customizable Targets: Includes multiple target types and configurations to vary gameplay scenarios. • Integration with ML-Agents: Built using Unity's ML-Agents framework for seamless AI training and deployment. • Reward System: Implements a reward mechanism to train the AI agent to prioritize accurate throws. • Training Capabilities: Allows users to train the AI agent in both simulation and real-time gameplay. • Visual Feedback: Provides real-time feedback on the AI's actions and performance.
What Unity version is ML Agents SnowballTarget compatible with?
ML Agents SnowballTarget is compatible with Unity versions 2018.4 and above.
Can I customize the snowy environment?
Yes, the environment and targets can be customized using Unity's built-in tools and assets.
How long does it take to train the AI agent?
Training time varies depending on the complexity of the task and the training parameters. Expect at least 15-30 minutes for basic training scenarios.