DESIGN METHODS FOR SCIENTIFIC HYPOTHESIS FORMATION AND THEIR APPLICATION TO MOLECULAR-BIOLOGY

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 a design problem. A program called HYPGENE designs hypotheses by reasoning backward from its goal of eliminating the difference between prediction and observation. This prediction error is eliminated by design 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 the HYPGENE 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.