srecord noeq ProbabilisticBinaryMaximumSearch(
  IProbabilisticScheduler scheduler,
  IF1<Double> scoreFunction,
  IVF1<Double> action,
  DoubleRange startRange) {
  double x;      // midpoint of current range
  double radius; // half the size of current range
  double minRadius = 1.0; // when to stop

  // sigmoid function (R to (0; 1))
  swappable double scoreToProbability(double score) {
    ret arctanSigmoid_zeroToOne(score);
  }
  
  swappable double recursionProbability() {
    ret zeroOne_double(radius <= minRadius);
  }
  
  void tryCandidate{
    x = (startRange.start+startRange.end)/2;
    radius = (startRange.end-startRange.start)/2;
    
    double score = scoreFunction.get(x);
    double p = scoreToProbability(score);
    scheduler.at(p, () -> action.get(x));

    scheduler.at(recursionProbability(), () -> split());
  }
  
  void split {
    radius /= 2;
    tryCandidate(x-radius);
    tryCandidate(x+radius);
  }
  
  void tryCandidate(double candidate) {
    double score = scoreFunction.get(candidate);
    double p = scoreToProbability(score);
    scheduler.at(p, () -> { x = candidate1; }
      
  }

  void walkLeft(double x) {
    Double y = map.lowerKey(x);
    if (y == null) ret;
    double p = distanceToProbability(abs(y-key));
    scheduler.at(p, () -> action.get(y));
    scheduler.at(p, () -> walkLeft(y));
  }

  void walkRight(double x) {
    Double y = map.higherKey(x);
    if (y == null) ret;
    double p = distanceToProbability(abs(y-key));
    scheduler.at(p, () -> action.get(y));
    scheduler.at(p, () -> walkRight(y));
  }
}