Home▸AI & Machine Learning▸Multi-Armed Bandit — Marketing Budget Allocator

Multi-Armed Bandit — Marketing Budget Allocator (2D)

Interactive 2D multi-armed bandit dashboard: watch epsilon-greedy and UCB1 algorithms allocate a marketing budget across five ad channels in real time, tracking live estimates, a cumulative-regret curve, and a spend-allocation strip as the algorithm learns which channel converts best.

AI & Machine Learning2DModerate60 FPS📱 Mobile-adapted⇄ 3D version

Details

CategoryAI & Machine Learning

RenderingCanvas 2D

DifficultyModerate

Target FPS60

ControlsChoose the allocation algorithm (epsilon-greedy / UCB1 / random baseline), tune the exploration rate ε and the allocation speed, pause/resume the run, toggle UCB confidence bounds and hidden true-rate markers on the bar panel, hover a bar for live per-channel detail, and reshuffle the five channels' hidden conversion rates for a new scenario.

machine learningreinforcement learningmulti-armed banditbusiness decisionsUCB1marketing analytics

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This simulator turns a classic reinforcement-learning problem — the multi-armed bandit — into a live marketing-budget dashboard. Five ad channels each hide a true, fixed conversion rate the algorithm cannot see. Every simulated budget unit is a "pull": a token drops from the budget source into the channel the current algorithm chose, landing as a win (green) or a miss (red) sampled from that channel's hidden rate. The top panel shows each channel's running estimate as a bar, the middle panel plots cumulative regret against the hindsight-optimal allocation over time, and the bottom strip shows how the budget has actually been split across channels so far. Switch between epsilon-greedy exploration, UCB1's confidence-bound exploration, and a random baseline, and watch all three panels respond together.

⚙ Under the hood

Watch epsilon-greedy, UCB1 and a random baseline compete to allocate a marketing budget across five ad channels with hidden conversion rates, tracking live estimates, a cumulative-regret curve and a spend-allocation strip in a layered 2D dashboard.

machine learningreinforcement learningmulti-armed banditbusiness decisionsUCB1marketing analytics

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