John F. Santore and Stuart C. Shapiro
This paper describes a cognitively plausible computational theory of identifying perceptually indistinguishable objects (PIOs) based on a set of experiments which were designed to identify the knowledge and perceptual cues that people use for this purpose. Identifying a PIO in this context means connecting sensor data from some physical object either to a new mental level symbol or to the correct preexisting one, and is part of the solution to the symbol anchoring problem. We discuss several base cases in the identification process, some related intermediate cases and the knowledge that is needed for the general case. An algorithm for identifying PIOs is included.