Design methods for scientific hypothesis formation and their application to molecular biology

Abstract

Hypothesis-formation problems occur when the outcome of an experiment as predicted by a scientific theory does not match the outcome observed by a scientist. The problem is to modify the theory, and/or the scientist's conception of the intial conditions of the experiment, such that the prediction agrees with the observation. I treat hypothesis formation as adesign problem. A program calledHypgene designs hypotheses by reasoning backward from its goal of eliminating the difference between prediction and observation. This prediction error is eliminated bydesign operators that are applied by a planning system. The synthetic, goal-directed application of these operators should prove more efficient than past generate-and-test approaches to hypothesis generation.Hypgene uses heuristic search to guide a generator that is focused on the errors in a prediction. The advantages of the design approach to hypothesis formation over the generate-and-test approach are analogous to the advantages of dependency-directed backtracking over chronological backtracking. These hypothesis-formation methods were developed in the context of a historical study of a scientific research program in molecular biology. This article describes in detail the results of applying theHypgene program to several hypothesis-formation problems identified in this historical study.Hypgene found most of the same solutions as did the biologists, which demonstrates that it is capable of solving complex, real-world hypothesis-formation problems.