Introduction

Eyal Kolman; Michael Margaliot

doi:10.1007/978-3-540-88077-6_1

Introduction

Eyal Kolman^*, Michael Margaliot

^*Corresponding author for this work

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Foreword/postscript

Abstract

In this chapter, we introduce some of the basic themes of this work. We begin with some background material on artificial intelligence and the paradigms of connectionism and symbolism. This is followed by a very brief review of artificial neural networks (ANNs) and fuzzy rule-based systems (FRBs). This sets the stage for the presentation of the main tool developed in this work, the fuzzy all-permutations rule-base (FARB). This is an FRB with a special form. This form guarantees that the input-output mapping of the FARB is mathematically equivalent to that of an ANN. This provides a new synergy between the learning-from-examples ability of ANNs and the high-level symbolic information processing of FRBs.

Original language	English
Title of host publication	Knowledge-Based Neurocomputing
Subtitle of host publication	A Fuzzy Logic Approach
Editors	Eyal Kolman, Michael Margaliot
Pages	1-12
Number of pages	12
DOIs	https://doi.org/10.1007/978-3-540-88077-6_1
State	Published - 2009

Publication series

Name	Studies in Fuzziness and Soft Computing
Volume	234
ISSN (Print)	1434-9922

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10.1007/978-3-540-88077-6_1

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Introduction

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