Procedural Puzzle Challenge Generation in Fujisan

Challenges for physical solitaire puzzle games are typically designed in advance by humans and limited in number. Alternately, some games incorporate stochastic setup rules, where the human solver randomly sets up the game board before solving the challenge, which can greatly increase the number of possible challenges. However, these setup rules can often generate unsolvable or uninteresting challenges. To better understand these setup processes, we apply a taxonomy for procedural content generation algorithms to solitaire puzzle games. In particular, for the game Fujisan, we examine how different stochastic challenge generation algorithms attempt to minimize undesirable challenges, and we report their affect on ease of physical setup, challenge solvability, and challenge difficulty. We find that algorithms can be simple for the solver yet generate solvable and difficult challenges, by constraining randomness through embedding sub-elements of the puzzle mechanics into the physical pieces of the game.