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Poor-Definition, Uncertainty, and Human Factors - Satisfying Multiple Objectives in Real-World Decision-Making Environments

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1993)

Abstract

Ill-definition, uncertainty and multiple objectives are primary characteristics of real-world decision-making processes. During the initial stages of such processes little knowledge appertaining to the problem at hand may be available. A primary task relates to improving problem definition in terms of variables, constraint and both quantitative and qualitative objectives. The problem space develops with information gained in a dynamical process where optimisation plays a secondary role following the establishment of a well-defined problem domain. The paper speculates upon the role of evolutionary computing, complementary computational intelligence techniques and interactive systems that support such problem definition where multiobjective satisfaction plays a major role.

Keywords

Problem Space Adaptive Filter Pareto Frontier Objective Preference Fuzzy Rule Base 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  1. 1.Advanced Computational TechnologiesExeterUK

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