Experiential learning in analogical problem solving

Abstract

A computational model of skill acquisition is analyzed based on extensions to an analogical problem solving method and previous Al work on concept acquisition. The present investigation focuses on exploiting and extending the analogical reasoning model to generate useful exemplary solutions to related problems from which more general plans can be induced and refined. Starting with a general analogical inference engine, problem solving experience is, in essence, compiled incrementally into effective procedures that solve various classes of problems in a more reliable and direct manner.