Dynamic Flexible Constraint Satisfaction and its Application to AI Planning / Edition 1

Dynamic Flexible Constraint Satisfaction and its Application to AI Planning / Edition 1

by Ian Miguel
     
 

Constraint satisfaction is a fundamental technique for knowledge representation and inference in Artificial Intelligence. This success is founded on simplicity and generality: a constraint simply expresses a set of admissible value combinations among a number of variables. However, the classical formulation of a static constraint satisfaction problem (CSP) with… See more details below

Overview

Constraint satisfaction is a fundamental technique for knowledge representation and inference in Artificial Intelligence. This success is founded on simplicity and generality: a constraint simply expresses a set of admissible value combinations among a number of variables. However, the classical formulation of a static constraint satisfaction problem (CSP) with inflexible constraints, all of which a solution must satisfy, is insufficient to model many real problems. This book demonstrates how a range of instances of these two powerful extensions can be combined in order to solve more complex problems.

Product Details

ISBN-13:
9781852337643
Publisher:
Springer London
Publication date:
11/14/2003
Series:
Distinguished Dissertations Series
Edition description:
2004
Pages:
318
Product dimensions:
0.81(w) x 6.14(h) x 9.21(d)

Table of Contents

List of Figures
1Introduction1
2The Constraint Satisfaction Problem13
3Dynamic Flexible Constraint Satisfaction65
4An Empirical Study of Fuzzy rrDFCSPs91
5Dynamic CSP in Domain-independent AI Planning159
6GP-rrDCSP: Experimental Results185
7Flexible Planning Problems & Flexible Graphplan203
8FGP: Experimental Results225
9Conclusion239
References251
APseudo-code263
BProofs271
CAn Empirical Study of Fuzzy rrDFCSPs: Complete Results279
DPlanning Problems281
Index315

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