Factorization in Experiment Generation

Devika Subramanian, Joan Feigenbaum

Experiment generation is an important part of incremental concept learning. One basic function of experimentation is to gather data to refine the existing space of hypotheses[DB83]. Here we examine the class of experiments that accomplish this, called discrimination experiments, and propose factoring as a technique for generating them efficiently.

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