A Good Snowman is Hard to Plan
Abstract
In this work we face a challenging puzzle video game: A Good Snowman is Hard to Build. The objective of the game is to build snowmen by moving and stacking snowballs on a discrete grid. For the sake of player engagement with the game, it is interesting to avoid that a player finds a much easier solution than the one the designer expected. Therefore, having tools that are able to certify the optimality of solutions is crucial. Although the game can be stated as a planning problem and can be naturally modelled in PDDL, we show that a direct translation to SAT clearly outperforms off-the-shelf state-of-the-art planners. As we show, this is mainly due to the fact that reachability properties can be easily modelled in SAT, allowing for shorter plans, whereas using axioms to express a reachability derived predicate in PDDL does not result in any significant reduction of solving time with the considered planners. We deal with a set of 51 levels, both original and crafted, solving 43 and with 8 challenging instances still remaining to be solved.
Cite
@article{arxiv.2310.01471,
title = {A Good Snowman is Hard to Plan},
author = {Miquel Bofill and Cristina Borralleras and Joan Espasa and Gerard Martín and Gustavo Patow and Mateu Villaret},
journal= {arXiv preprint arXiv:2310.01471},
year = {2023}
}
Comments
arXiv admin note: text overlap with arXiv:2310.01378