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🔍 Claim-Evidence Bayesian Belief Network (2D)

2D Bayesian reasoning lab: a claim node with a prior probability updates through real sequential Bayes' theorem math as you toggle evidence nodes true/false and tune each likelihood ratio, live on a posterior belief meter.

Cognitive Science2DModerate60 FPS📱 Mobile-adapted⇄ 3D version

This 2D companion turns the same claim-evidence idea from the 3D version into a real, checkable Bayesian calculation: a claim node carries a prior probability, four evidence nodes each carry a likelihood ratio, and toggling a node TRUE/FALSE/UNKNOWN runs a genuine sequential Bayes' theorem update in log-odds space — prior odds times each active evidence's likelihood ratio, renormalized back to a posterior probability — so the belief meter always reflects an actual, hand-verifiable computation rather than a cosmetic animation.

⚙ Under the hood

2D Bayesian belief-network lab: a claim's prior probability is updated through real sequential Bayes' theorem math (log-odds accumulation of each active evidence's likelihood ratio) as evidence nodes are toggled true, false or left unknown.

bayesian inferencebelief networklikelihood ratiocritical thinkingprobabilistic reasoninglog-odds

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