A cognitive system based on fuzzy information processing and multi-objective evolutionary algorithm

A cognitive system is presented, which is based on coupling a multi-objective evolutionary algorithm with a fuzzy information processing system. The aim of the system is to identify optimal solutions for multiple criteria that involve linguistic concepts, and to systematically identify a most suitab...

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Vydáno v:2009 IEEE Congress on Evolutionary Computation s. 1271 - 1280
Hlavní autoři: Bittermann, M.S., Ciftcioglu, O., Sariyildiz, I.S.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.05.2009
Témata:
Cognition
cognitive design
Decision making
Design optimization
Diversity methods
Evolutionary computation
fuzzy neural tree
Fuzzy systems
Humans
Information processing
Knowledge representation
multi-objective optimization
Pareto front
Pareto optimization
soft computing
ISBN:1424429587, 9781424429585
ISSN:1089-778X
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Shrnutí:A cognitive system is presented, which is based on coupling a multi-objective evolutionary algorithm with a fuzzy information processing system. The aim of the system is to identify optimal solutions for multiple criteria that involve linguistic concepts, and to systematically identify a most suitable solution among the alternatives. The cognitive features are formed by the integration of fuzzy information processing for knowledge representation and evolutionary multi-objective optimization resulting in a decision-making outcome among several equally valid options. Cognition is defined as final decision-making based not exclusively on optimization outcomes but also some higher-order aspects, which do not play role in the pure optimization process. By doing so, the decisions are not merely subject to rationales of the computations but they are the resolutions with the presence of environmental considerations integrated into the computations. The work describes a novel fuzzy system structure serving for this purpose and a novel evolutionary multi-objective optimization strategy for effective Pareto-front formation serving for the goal. The machine cognition is exemplified by means of a design example, where a number of objects are optimally placed according to a number of architectural criteria.
ISBN:1424429587
9781424429585
ISSN:1089-778X
DOI:10.1109/CEC.2009.4983091