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IndisputableMonolith.Decision.MontyHall

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The MontyHall module supplies the sample space and counting machinery for the Monty Hall decision problem inside Recognition Science. It defines the joint outcome of prize location and initial pick, then builds the stay and switch winning sets together with their cardinalities and probabilities. The module is used by any RS analysis that compares decision strategies under the cost structure. It is a pure definition module containing no proofs.

claimLet $Outcome$ be the set of pairs (prize location, initial pick). Define $stayWinningSet, switchWinningSet$ as the subsets of winning outcomes under each strategy, with $p_{stay} = |stayWinningSet| / |Outcome|$ and $p_{switch} = |switchWinningSet| / |Outcome|$.

background

The module sits in the Decision domain and imports the RS time quantum τ₀ = 1 tick from Constants together with the cost formalism from the Cost module. Its central object is Outcome, the joint outcome consisting of prize location and the player's initial pick. From Outcome it derives outcome_count, the finite cardinality of the sample space, the subsets StayWins and SwitchWins, their cardinalities stayWinningSet_card and switchWinningSet_card, and the two probability values p_stay and p_switch.

proof idea

This is a definition module, no proofs.

why it matters in Recognition Science

The module provides the concrete Monty Hall model that feeds decision-theoretic comparisons under the Recognition Composition Law. It supplies the probability objects that any later theorem on optimal switching strategies would cite. No downstream theorems are recorded in the current dependency graph.

scope and limits

depends on (2)

Lean names referenced from this declaration's body.

declarations in this module (25)