Proceedings of the Annual Meeting of the Cognitive Science Society

The present paper explores the relationship between a process/mathematical model and aconnectionist model of pattern recognition. In both models, pattern recognition is viewed ashaving available multiple sources of infomiation supporting the identification and interpretationof the input The results from a wide variety of experiments have been described within theframework of a fuzzy logical model of perception. The assumptions central to this process modelare 1) each source of infonnation is evaluated to give the degree to which that source specifiesvarious alternatives, 2) the sources of information are evaluated independently of one another, 3)the sources are integrated to provide an overall degree of support for each alternative, and 4)percepmal identification and interpretation follows the relative degree of support among thealternatives. Connectionist models have been successful at describing the same phenomena.These models assume interactions among input, hidden, and output units that activate and inhibitone another. Similarities between the frameworks are described, and the relationship betweenthem explored. A specific connectionist model with input and output layers is shown to bemathematically equivalent to the fuzzy logical model. It remains to be seen which frameworkserves as the better heuristic for psychological inquiry.