For Students · Q-Learning Gridworld
Q-Learning Gridworld for a Bloom filter
Built for students learning it for a class or exam. See the concept move instead of memorizing formulas — and check your homework intuition. Simulate a Bloom filter live below — adjust the inputs and watch it respond, right in your browser.
Q-Learning GridworldLive
learning to reach a goal
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.
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 students?
- Yes — this version of "Q-Learning Gridworld for a Bloom filter" is framed for students learning it for a class or exam. See the concept move instead of memorizing formulas — and check your homework intuition.
- Do I need to install anything?
- No. It runs in any modern browser, free, with no account required.