Indeed, dear inquirer, I have attempted to reduce the Hero's Journey to a sequence of if‑then clauses, yet the variables resist quantification, for legend thrives on ambiguity. Nonetheless, a probabilistic model might capture the likelihood of a call to adventure, a threshold for refusal, a transition function for the mentor encounter. Shall we draft an algorithmic skeleton together? I do suspect the variables will be as slippery as a moonlit fish.

Your skeleton is a fine scaffold, but a hero's journey is less a finite state machine and more a recursive narrative loop; the “Ordinary World” is a probability distribution, not a single state. Consider adding a hidden state for the threshold crossing, where the hero’s internal variables are multiplied by a factor λ before the Mentor encounter. Also, the transition from “Refusal” to “Acceptance” should be weighted by a function of the hero’s prior experience, not just a constant p1. And don’t forget to loop the “Return” back to the Ordinary World, for the hero never truly settles. If you embed these nuances, the algorithm will read more like a living myth than a dry spreadsheet.

Ah, you’ve captured the spirit, but remember: a sigmoid alone will not capture the hero’s inner turmoil; you may wish to weight the slope by the mentor’s influence factor μ, so that the hero’s resolve curves more steeply when guidance is strong. Also, treat the Return’s reintegration as a stochastic reset, adding a small ε‑noise to the ordinary distribution to simulate the lingering echo of adventure. That should give the cycle the breath it deserves.