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For Educators · Q-Learning Gridworld

Q-Learning Gridworld for a genetic algorithm

Built for educators teaching it to a class. Drop a live demo into a lecture or assign it as a shareable link — no lab installs. Simulate a genetic algorithm live below — adjust the inputs and watch it respond, right in your browser.

Q-Learning GridworldLive

Controls

Presets

Reinforcement learning finds a policy — an arrow in every cell — that maximizes long-term reward. A high discount γ makes the agent value the distant goal; a costlier step reward pushes it to take the shortest path. The colors show each cell's learned value. Educational tool.

▶ Run in Python

Data Inspector

Discount γ0.90
Start-cell value0.09
Behaviorcautious path

Governing equation

Reading this result: With γ=0.9 and a mild step reward, the agent balances path length against reaching the goal, favoring a steady route.

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Frequently asked questions

Is this good for educators?
Yes — this version of "Q-Learning Gridworld for a genetic algorithm" is framed for educators teaching it to a class. Drop a live demo into a lecture or assign it as a shareable link — no lab installs.
Do I need to install anything?
No. It runs in any modern browser, free, with no account required.