Abstract
Single-agent search is a powerful tool for solving a variety of applications. Most of the academic application domains used to explore single-agent search techniques have the property that if you start with a solvable state, at no time in the search can you reach a state that is unsolvable (it may, however, not be minimal). In this paper we address the implications that arise when states in the search are unsolvable. These so-called deadlock states are largely responsible for the failure of our attempts to solve positions in the game of Sokoban.
This is a revised and updated version of a paper presented at the IJCAI workshop on Using Games as an Experimental Testbed for Artificial Intelligence Research, Nagoya, August, 1997.
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Junghanns, A., Schaeffer, J. (1998). Sokoban: Evaluating standard single-agent search techniques in the presence of deadlock. In: Mercer, R.E., Neufeld, E. (eds) Advances in Artificial Intelligence. Canadian AI 1998. Lecture Notes in Computer Science, vol 1418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64575-6_36
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DOI: https://doi.org/10.1007/3-540-64575-6_36
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