Heuristic search has been successful for games like chess and checkers, but seems to be of limited value in games such as Go and shogi, and puzzles such as Sokoban. Other techniques are necessary to approach the performance that humans achieve in these hard domains. This paper explores using planning as an alternative problem-solving framework for Sokoban. Previous attempts to express Sokoban a...

The game of Sokoban is an interesting platform for algorithm research. It is hard for humans and computers alike. Even with its simple rules and small average level sizes there are levels that take a lot of computation for all known algorithms. In this thesis we will combine different Sokoban solvers with different domain specific enhancements into one portfolio. This portfolio can then be run ...

Sokoban puzzle is very challenging problem for both humans and computers. It also illustrates differences between human and artificial intelligence – different problems are difficult for humans and for computers. Whereas algorithmic techniques for Sokoban solving have been intensively studied by previous research, factors determining difficulty for humans have not been sufficiently explained so...

This paper describes our program that makes Sokoban problems automatically. Sokoban is one of one-person puzzles invented in Japan. The program consists of three stages: generation, checking and evaluation. First, candidates for problems are generated randomly by a prototype and three templates . Second, unsolvable candidates are removed by the Sokoban solver. Finally trivial or uninteresting c...

We present a novel admissible pattern database heuristic (D) and tie-breaking rule (L) for Sokoban, allowing us to increase the number of optimally solved standard Sokoban instances from 20 to 28 and the number of proved optimal solutions from 25 to 32 compared to previous methods. The previously best heuristic for Sokoban (I) used the idea of an intermediate goal state to enable the effective ...

Evidence is provided that players pay at least as much attention to a set of procedurally generated Sokoban levels as they do to levels hand crafted by expert designers. Data were collected from 40 participants who played Sokoban under laboratory conditions while simultaneously performing an auditory Stroop test. Three performance measures from the Stroop test were analyzed and compared after a...

This paper reports on an attempt to come closer to an understanding of understanding, in the domain of artificial intelligence. Our approach is based in the idea that understanding means exploiting underlying structure. Our goal is compact code that is adapted to the structure of its problem domain. We want to achieve this compactness by applying Occam’s Razor in an evolutionary framework. As a...

This article describes a new method for attempting to solve Sokoban puzzles by means of an efficient algorithm, a task which has proven to be extremely difficult because of both the huge search tree depth and the large branching factor. We present a way of solving Sokoban puzzles that, using several heuristics, starts from the final state of a puzzle, and from there works its way back to the in...

This bachelor thesis describes a new method for attempting to solve Sokoban puzzles by means of an efficient algorithm, a task which has proven to be extremely difficult because of both the huge search tree depth and the large branching factor. We present a way of solving Sokoban puzzles that, using several heuristics, starts from the final state of a puzzle, and from there works its way back t...

We consider a natural family of motion planning problems with movable obstacles and obtain hardness results for them. Some members of the family are shown to be PSPACE-complete thus improving and extending (and also simplifying) a previous NP-hardness result of Wilfong. The family considered includes a motion planning problem which forms the basis of a popular computer game called SOKOBAN. The ...