Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence (IJCAI-93), pp. 1135-1140, Chambéry, France, July 1993.
Paper ID: 26
Category: Theory and Knowledge Refinedment
This paper presents a major revision of the EITHER propositional theory refinement system. Two issues are discussed. First, we show how run time efficiency can be greatly improved by changing from a exhaustive scheme for computing repairs to an iterative greedy method. Second, we show how to extend EITHER to refine M-of-N rules. The resulting algorithm, NEITHER (New EITHER), is more than an order of magnitude faster and produces significantly more accurate results with theories that fit the M-of-N format. To demonstrate the advantages of NEITHER, we present preliminary experimental results comparing it to EITHER and various other systems on refining the DNA promoter domain theory.
