The Sokoban Random Walk: A Trapping Perspective
Abstract
We study caging/trapping in Sokoban-type models, featuring a random walker moving through a disordered medium of obstacles and capable of pushing some obstacles blocking its path. In one-dimension, we allow the walker to push up to an arbitrary number of obstacles. For , we use large-deviation theory to show that the survival probability to remain uncaged exhibits crossover from an exponential decay with time at intermediate times to a stretched-exponential decay at long times, with an exponent independent of . The long-time exponent matches the Balagurov--Vaks--Donsker--Varadhan (BVDV) theory of the classical trapping problem, while the exponential decay is qualitatively distinct from the Rosenstock's intermediate-time theory for classical trapping. Similarly, in two dimensions, numerical simulations reveal that both the Sokoban model and its generalized version exhibit long-time stretched-exponential relaxation with exponent , again consistent with the BVDV theory. Finally, in two dimensions, we find that the mean trap size is nonmonotonic in : it is small at both low and high densities, but reaches a peak at a characteristic density . We estimate for the Sokoban model and for the generalized Sokoban model.
Keywords
Cite
@article{arxiv.2602.14180,
title = {The Sokoban Random Walk: A Trapping Perspective},
author = {Prashant Singh and Eli Barkai and David A Kessler},
journal= {arXiv preprint arXiv:2602.14180},
year = {2026}
}