PROBLEM-SOLVING MODELS AND SEARCH STRATEGIES FOR PATTERN-RECOGNITION

Notingthe major limitations of multivariate statistical classification and syntactic pattern recognition models, this paper presents an overview of some recent work using alternate representations for multistage and nearest neighbor multiclass classification, and for structural analysis and feature extraction. These alternate representations are based on generalizations of state-space and AND/OR graph models and search strategies developed inartificial intelligence (AI). The paper also briefly touches on other current interactions and differences between artificial intelligence and pattern recognition. Copyright © 1979 by The Institute of Electrical and Electronics Engineers, Inc.