Result: Solving collaborative fuzzy agents problems with CLP(FD)

Title:
Solving collaborative fuzzy agents problems with CLP(FD)
Source:
PADL 2005 : practical aspects of declarative languages (Long Beach CA, 10-11 January 2005)Lecture notes in computer science. :187-202
Publisher Information:
Berlin: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 22 ref
Original Material:
INIST-CNRS
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
School of Computer Science, Technical University of Madrid (UPM), Spain
ISSN:
0302-9743
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.16547098
Database:
PASCAL Archive

Further Information

Truth values associated to fuzzy variables can be represented in an ordeal of different flavors, such as real numbers, percentiles, intervals, unions of intervals, and continuous or discrete functions on different domains. Many of the most interesting fuzzy problems deal with a discrete range of truth values. In this work we represent these ranges using Constraint Logic Programming over Finite Domains (CLP(FD)). This allows to produce finite enumerations of constructive answers instead of complicated, hardly self-explanatory, constraints expressions. Another advantage of representing fuzzy models through finite domains is that some of the existing techniques and algorithms of the field of distributed constraint programming can be borrowed. In this paper we exploit these considerations in order to create a new generation of collaborative fuzzy agents in a distributed environment.