Qualitative model evolution
Alen Varšek · 1991
A genetic algorithm is used for learning qualitative model* baaed on the QSIM formalism. Hierarchical representation enables formation of "submodels " relevant for induction of domain explanation. Daring the search for better coding of the candidates, in parallel with the search for better solutions, the sise and shape of candidate solutions are dynamically created. Optimisation is based on the maximisation of the number of examples covered by a candidate solution combined with the minimisation of the number of constraints used in the solution. The result of learning is a set of models of different specificity that explain all given examples. An experiment in learning a qualitative model of the connected container system (U-TUBE) is described in detail. Several solutions, equivalent to the original model, were discovered. 1