How to resolve the algorithm 100 prisoners step by step in the Pointless programming language

Published on 12 May 2024 09:40 PM
#Pointless

How to resolve the algorithm 100 prisoners step by step in the Pointless programming language

Table of Contents

Problem Statement

Show and compare the computed probabilities of success for the two strategies, here, on this page.

Let's start with the solution:

Step by Step solution about How to resolve the algorithm 100 prisoners step by step in the Pointless programming language

Source code in the pointless programming language

optimalSeq(drawers, n) =
  iterate(ind => drawers[ind - 1], n)
  |> takeUntil(ind => drawers[ind - 1] == n)

optimalTrial(drawers) =
  range(1, 100)
  |> map(optimalSeq(drawers))

randomSeq(drawers, n) =
  iterate(ind => randRange(1, 100), randRange(1, 100))
  |> takeUntil(ind => drawers[ind - 1] == n)

randomTrial(drawers) =
  range(1, 100)
  |> map(randomSeq(drawers))

checkLength(seq) =
  length(take(51, seq)) <= 50

numTrials = 3000

runTrials(trialFunc) =
  for t in range(1, numTrials)
  yield
    range(1, 100)
    |> shuffle
    |> toArray
    |> trialFunc
    |> map(checkLength)
    |> all

countSuccess(trialFunc) =
  runTrials(trialFunc)
  |> filter(id)
  |> length

optimalCount = countSuccess(optimalTrial)
randomCount = countSuccess(randomTrial)

output =
  format("optimal: {} / {} = {} prob\nrandom: {} / {} = {} prob", [
    optimalCount, numTrials, optimalCount / numTrials,
    randomCount, numTrials, randomCount / numTrials,
  ])
  |> println

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