This paper describes Tabletop, a computer progam that models human analogy-making in a micro-world consisting of a small table covered with ordinary table objects. We argue for the necessity, even in this simple domain, of an architecture that builds its own representations by means of a continual interaction between an associative network of fixed concepts (the Slipnet) and simple low-level perceptual agents (codelets), that relies on local processing and (simulated) parallelism, and that is fundamentally stochastic. Several problems solved by the Tabletop program are used to illustrate these principles.
