integrating Marker Passing and Problem Solving: A Spreading Activation Approach To Improved Choice in Planning

by James A. Hendler

Overview

A recent area of interest in the Artificial Intelligence community has been the application of massively parallel algorithms to enhance the choice mechanism in traditional AI problems. This volume provides a detailed description of how marker-passing — a parallel, non-deductive, spreading activation algorithm — is a powerful approach to refining the choice mechanisms in an AI problem-solving system.

The author scrutinizes the design of both the algorithm and the system, and then reviews the current literature and research in planning and marker passing. Also included: a comparison of this computer model with some standard cognitive models, and a comparison of this model to the "connectionist" approach.

Product Details

ISBN-13:	9780898599824
Publisher:	Taylor & Francis
Publication date:	11/01/1987
Series:	Artificial Intelligence Series
Pages:	318
Product dimensions:	6.00(w) x 9.00(h) x (d)
Lexile:	1260L (what's this?)

About the Author

James A. Hendler Department of Computer Science, The University of Maryland

Table of Contents

Contents: Foundations. Introduction. On Problem-Solving and Planning. On Marker-Passing and Spreading Activation. Integrating Marker-Passing and Problem-Solving — The Inside Story. Inside the Path Evaluator. Designing a Marker-Passer. C-SCRAPS — Adding Concurrency. Cognitive Aspects. On Marker-Passing and Connectionism. SCRAPS in Action. Conclusion.