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In this paper we describe two properties of most psychological and AI models of scientific problem solving: they are one-peiss, and feed forward. W e then discuss the results of an experiment which suggests that experts use problem solving representations more flexibly than these models suggest. W e introduce the concept of incremental envisioning to account for this flexible behavior. Finally, we discuss the implications of this work for psychological models of scientific problem solving and for AI programs which solve problems in scientific domains.
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