Towards a practical theory of reformulation for reasoning about physical systems

In this paper, we propose a practical framework for characterizing, evaluating and selecting reformulation techniques for reasoning about physical systems, with the long-term goal of automating the selection and application of these techniques. We view reformulation as a mapping from one encoding of a problem to another. A problem-solving task is in turn accomplished by the application of a sequence of reformulations to an initial problem encoding to produce a nal encoding that addresses the task. Our framework provides the terminology to specify the conditions under which a particular reformulation technique is applicable, the cost associated with performing the reformulation, and the e ects of the reformulation with respect to the problem encoding. As such it provides the vocabulary to characterize the selection of a sequence of reformulation techniques as a planning problem. Our framework is su ciently exible to accommodate previously proposed properties and metrics for reformulati...

• Type: Journal
• Year: 2005
• Where: AI
• Authors: Berthe Y. Choueiry, Yumi Iwasaki, Sheila A. McIlraith
• Keywords: AI 2005, Artificial Intelligence, Physical Systems, Practical Framework, Reformulation Techniques