Paradigms of Artificial Intelligence: A Methodological and Computational Analysis

This book presents a new methodological analysis of the two competing research paradigms of artificial intelligence and cognitive science: the symbolic versus the connectionist paradigm. It argues that much of the discussion put forward for either paradigm misses the point: Most of the arguments in the debates on the two paradigms concentrate on the question whether the nature of intelligence or cognition is properly accommodated by one or the other paradigm. Opposed to that is the analysis in this book, which concentrates on the question which of the paradigms accommodates the "user" of a developed theory or technique. The user may be an engineer or a scientist - in any case, the "user" has to be able to grasp the theory and to competently use the methods which are developed. Consequently, besides the nature of intelligence and cognition, the "user" must be the focus of the debate on the proper paradigm. From the relationship between the mental capacities of the "user" and certain aspects of the nature of intelligence and cognition, the book derives new objectives for future research which will help to integrate aspects of both paradigms to obtain more powerful AI techniques and to promote a deeper understanding of cognition. . The book presents the fundamental ideas of both, the symbolic as well as the connectionist paradigm. Along with an introduction to the philosophical foundations, an exposition of some of the typical techniques of each paradigm is presented in the first two parts. This is followed by the mentioned analysis of the two paradigms in the third part. The book is intended for researchers, practitioners, advanced students, and interested observers of the developing fields of artificial intelligence and cognitive science. Providing accessible introductions to the basic ideas of both paradigms, it is also suitable as a textbook for a subject on the topic at an advanced level in computer science, philosophy, cognitive science, or psychology.

Table of Contents:
Preface.- Introduction.- The Symbolic Paradigm: Foundations of the Symbolic Paradigm. Knowledge Representation and Reasoning. Knowledge-Based Systems - Expert Systems. Symbolic Learning. Summary of the Symbolic Paradigm. The Connectionist Paradigm: Foundations of the Connectionist Paradigm. Connectionist Computing Models. Integrating Symbols into Connectionist Models. Summary of the Connectionist Paradigm.- Methodological Analysis of the two Paradigms: Formal Foundations. Levels of Description. The Notion of 'Symbols'. Computational Limitations of Connectionist Computing Models. Methodological Discussion. Non-Factual Knowledge. Conclusions.- Appendix.