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Notification Channel Optimizer — Multi-Armed Bandit Live

Watch a multi-armed bandit AI learn, message by message, which channel (SMS, email, app push, mail) most reliably reaches citizens for government alerts — compare epsilon-greedy against UCB1 in real time.

AI & Machine Learning3DModerate60 FPS📱 Mobile-adapted⇄ 2D version

A government agency needs to send a citizen alert, but which channel — SMS, email, app push, or mail — will actually get read? This simulator runs a real multi-armed bandit AI that sends one synthetic message at a time, observes whether it was "opened" against a hidden per-channel true rate, and updates its running belief. Switch between epsilon-greedy and UCB1 selection strategies and watch the four channel towers rise and settle in 3D as the AI converges on the best-performing channel, with live cumulative-regret and open-rate readouts tracking how efficiently it's learning.

⚙ Under the hood

An interactive multi-armed bandit simulator where an AI system learns, message by message, which communication channel — SMS, email, app push, or mail — most reliably reaches citizens for government alerts, comparing epsilon-greedy against UCB1 exploration strategies in real time.

AIgovernmentmulti-armed banditreinforcement learningcitizen engagementoptimization

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install