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A connectionist processing metaphor for diagnostic reasoning
Author(s) -
Ahuja Sanjeev B.,
Soh WooYoung,
Schwartz Al
Publication year - 1989
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.4550040204
Subject(s) - connectionism , metaphor , computer science , artificial intelligence , cognitive science , natural language processing , artificial neural network , psychology , linguistics , philosophy
This article describes LIBRA/Dx, a competition‐based parallel activation model for diagnostic reasoning. Within a causal network, the model uses a neurally inspired processing paradigm to generate the most plausible explanation for a set of observed manifestations. the model was built using LIBRA: a domain‐independent parallel activation network generator, that can be used to build network models with processing paradigms that are tailored to the specifics of an application domain. the underlying theory postulates that by simultaneously satisfying multiple constraints that may exist locally among domain concepts in a causal network (e.g., among disorders, syndromes, manifestations, etc.) it is possible to construct a plausible global explanation for a set of observed signs and symptoms. the proposed processing paradigm which uses an associative network of concepts to represent domain knowledge, lends itself to the kind of interactive processing that is necessary to capture the generative capacity of human diagnostic ability in novel situations. LIBRA/Dx offers a new approach to modeling a higher cognitive process: diagnostic reasoning, specifically in terms of the time‐course of processing and the nature of knowledge representation. It further contributes to our current understanding of the phenomena of human cognition, which have eluded successful explication in conventional computational formalisms.