Structure-mapping engine enables computers to reason and learn like humans, including solving moral dilemmas
Northwestern Engineering’s Ken Forbus is closing the gap between humans and machines.
Using cognitive science theories, Forbus and his collaborators have developed a model that could give computers the ability to reason more like humans and even make moral decisions. Called the structure-mapping engine (SME), the new model is capable of analogical problem solving, including capturing the way humans spontaneously use analogies between situations to solve moral dilemmas.
“In terms of thinking like humans, analogies are where it’s at,” said Forbus, Walter P. Murphy Professor of Electrical Engineering and Computer Science in Northwestern’s McCormick School of Engineering. “Humans use relational statements fluidly to describe things, solve problems, indicate causality, and weigh moral dilemmas.”
The theory underlying the model is psychologist Dedre Gentner’s structure-mapping theory of analogy and similarity, which has been used to explain and predict many psychology phenomena. Structure-mapping argues that analogy and similarity involve comparisons between relational representations, which connect entities and ideas, for example, that a clock is above a door or that pressure differences cause water to flow.
Analogies can be complex (electricity flows like water) or simple (his new cell phone is very similar to his old phone). Previous models of analogy, including prior versions of SME, have not been able to scale to the size of representations that people tend to use. Forbus’s new version of SME can handle the size and complexity of relational representations that are needed for visual reasoning, cracking textbook problems, and solving moral dilemmas.