AAAI 1986
Factorization in Experiment Generation
Abstract
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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Context
- Venue
- AAAI Conference on Artificial Intelligence
- Archive span
- 1980-2026
- Indexed papers
- 28718
- Paper id
- 11213988485739478