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🧪 Reinforcement Learning Explained — Agents, Rewards, and Value

Explainer of reinforcement learning with agents, rewards, value functions, policy/value iteration, Q-learning, examples, and FAQ.

Machine Learning & Neural Networks2DModerate60 FPS

⚙ Under the hood

This simulation introduces the core concepts of reinforcement learning. It illustrates how agents learn optimal actions through trial and error, guided by rewards and value functions within an environment.

Reinforcement LearningAgents Rewards

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install