Abstract

Problem solving is an analog to scientific method, wherein abduction and deduction operate in a cyclic fashion to generate and refine a series of hypotheses that purport to explain the observed data. Model generative reasoning implements this cycle through a family of operations on representations based on conceptual graphs. Specialize, the operator that implements abduction, generates alternative hypotheses. Fragment removes potential incoherences from hypotheses, while preserving coherence with the observations. This is seen as a form of deduction with the aim of allowing more hypotheses to be generated in the next cycle.

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