Universal Planning: An (Almost) Universally Bad Idea

Matthew L. Ginsberg

Abstract


Several authors have recently suggested that a possible approach to planning in uncertain domains is to analyze all possible situations beforehand and then store information about what to do in each. The result is that a system can simply use its sensors to examine its domain and then decide what to do by finding its current situation in some sort of a table. The purpose of this article is to argue that even if the compile-time costs of the analysis are ignored, the size of the table must, in general, grow exponentially with the complexity of the domain. This growth makes it unlikely that this approach to planning will be able to deal with problems of an interesting size; one really needs the ability to do some amount of inference at run time. In other words, an effective approach to acting in uncertain domains cannot be to look and then leap; it must always be to look, to think, and only then to leap.

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DOI: http://dx.doi.org/10.1609/aimag.v10i4.964

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