Play and train agents in an interactive pyramid game
EnjoyGame
Play web-based vehicle physics simulations using WASD controls
Run an interactive Unity game
Interact with a web-based physics vehicle simulation using WASD keys
Control and simulate a physics-based vehicle in a web browser
PlayPhysics - Control a vehicle using WASD
"One-minute creation by AI Coding Autonomous Agent MOUSE-I"
Play trivia questions to earn points
Play an interactive 3D Breakout game
Experience a physics-based vehicle simulation
Play Wordle by guessing letters
Simulate vehicle physics with WASD controls
ML Agents Pyramids is an interactive Game AI application designed for training and playing with intelligent agents in a pyramid-based game environment. It provides a unique space for experimenting with AI decision-making and learning behaviors in a structured, goal-oriented setting. Whether you're a researcher, developer, or casual gamer, ML Agents Pyramids offers a fun and educational experience for exploring AI capabilities.
• Interactive Game Environment: Engage with a pyramid-shaped board where agents can move and make decisions.
• Real-Time Feedback: Observe agent behavior and outcomes as they navigate the pyramid.
• Customizable Scenarios: Adjust game rules, agent goals, and pyramid configurations to test various AI strategies.
• Multiple Training Modes: Choose between supervised learning, reinforcement learning, or imitation learning approaches.
• Visualization Tools: Track agent performance, learning curves, and decision-making processes in real time.
What type of AI models can I train with ML Agents Pyramids?
You can train models using reinforcement learning, imitation learning, or supervised learning methods, depending on your goals.
Do I need prior knowledge of machine learning to use ML Agents Pyramids?
While some understanding of AI concepts is helpful, the tool is designed to be accessible to both beginners and experts.
Can I customize the game rules or pyramid structure?
Yes, ML Agents Pyramids allows you to modify game rules and adjust pyramid configurations to suit your experimental needs.