Information Fusion and Logic-based Reasoning
Approaches for Decision Making under Uncertainty
J.UCS Special Issue
Luis Martínez
(Department of Computer Science, University of Jaén
23071 Jaén, Spain
martin@ujaen.es)
Jun Liu
(School of Computing and Mathematics, University of Ulster
Northern Ireland, UK
j.liu@ulster.ac.uk)
Yang Xu
(School of Mathematics, Southwest Jiaotong University
Chengdu, Sichuan 610031, P.R. China
xuyang@home.swjtu.edu.cn)
Decision Making is a core area in different research fields related to
human beings' intelligent activities; such activities involve
different types of uncertainties depending on its nature. Therefore,
different methods, models and formalisms have been investigated and
applied to a wide range of decision making problems under uncertainty.
This special issue is devoted to information fusion models and
logic based formalisms and their application to decision making under
uncertainty, it encompasses eleven papers.
The first paper Some Views on Information
Fusion and Logic Based Approaches in Decision Making under
Uncertainty establishes the framework of this special issue,
making a review of the state of art and pointing out different open
problems and research opportunities in the topic. Salguero and
Araque then propose an integration process based on the OWA
operator taking into account temporal characteristics of the data. And
Oussalah et al.
address a track-to-track fusion problem.
In the paper A
Selection Process Based on Additive Consistency to Deal with
Incomplete Fuzzy Linguistic Information, Cabrerizo et al. manage
missing values in decision making problems. Kahraman et al.
present a new approach for a selection process for renewable energies
and Ruan et al.
a decision support system to analyze long-term energy policies. And in
A Demand
Forecasting Methodology for Fuzzy Environments a fuzzy demand
forecast methodology is introduced.
Mingyi et al.
explore fuzzy semi-equivalence relations and its properties in
decision reasoning processes. Meanwhile, Yang and Xu
introduce a lattice-valued logic decision model.
Eventually Kołaczek and
Juszczyszyn present a multi-ontology framework for multi-agent
systems based on deontic logic and Châtel et al. provide
a graphical model based on LCP-nets and its logic formalism to model
non-functional properties in order to be applied to the dynamic
selection of web services.
Luis Martínez, Jaén, Spain
Jun Liu, Ulster, UK
Yang Xu
Chengdu, P.R. China
December 2009
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