Proceedings of the Annual Meeting of the Cognitive Science Society

Tabletop is a computer model of analogy-making that has a nondeterministic parallel architecture. It is based on the premise that analogy-making is a by-product of high-level perception, and it operates in a restricted version of an everyday domain: that of place-settings on a table. The domain's simplicity helps clarify the tight link between perception and analogy-making. In each problem, a table configuration is given; the user, hypothetically seated at the table, points at some object. The program responds by doing "the same thing", as determined from the opposite side of the table. Being nondeterministic, Tabletop acts differently when run repeatedly on any problem. Thus to understand how diverse pressures affect the program, one must compile statistics of many runs on many problems. Tabletop was tested on several families of interrelated problems, and a performance landscape was built up, representing its "likes" and "dislikes". Through qualitative comparisons of this landscape with human preferences, one can assess the psychological realism of Tabletop's "uste".