NDLI: Rational behavior design using multi-selective generation

Content Provider	IEEE Xplore Digital Library
Author	Menezes, A.A. Kabamba, P.T.
Copyright Year	2010
Description	Author affiliation: Department of Aerospace Engineering at the University of Michigan, Ann Arbor, 48109, USA (Menezes, A.A.; Kabamba, P.T.)
Abstract	This paper extends a technique that solves a generalization of the standard global optimization problem: instead of generating the optimizer, the technique produces, on the search space, a probability density function referred to as the behavior. The generalized solution depends on a parameter, the level of selectivity, such that as this parameter tends to infinity, the behavior becomes a delta function at the location of the optimizer. The motivation for this generalization is that traditional off-line global optimization is unresponsive to perturbations of the objective function. Although the original technique achieves responsive optimization, a large number of iterations may be required. In most instances, the extended technique of this paper, which is known as multi-selective generation, averages fewer iterations to achieve responsive optimization. Multi-selective generation is formulated here to generalize the canonical genetic algorithm with fitness proportional selection. Necessary and sufficient conditions that are required by multi-selective generation to achieve so-called rational behavior are specified. Rational behavior is desirable because it can lead to both efficient search and responsive optimization. However, the conditions for the extended technique to behave rationally are highly restrictive. The implication is that the original technique, which behaves rationally, is preferable for efficient search and responsive optimization.
Starting Page	3938
Ending Page	3943
File Size	167221
Page Count	6
File Format	PDF
ISBN	9781424477456
ISSN	07431546
e-ISBN	9781424477463
DOI	10.1109/CDC.2010.5717419
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-12-15
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Markov processes Optimization Convergence Entropy Probability distribution Eigenvalues and eigenfunctions Evolutionary computation
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Modeling and Simulation

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