Proceedings ArticleDOI
On genetic algorithms
Eric B. Baum,Dan Boneh,Charles Garrett +2 more
- pp 230-239
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TLDR
C Culling is near optimal for this problem, highly noise tolerant, and the best known a~~roach in some regimes, and some new large deviation bounds on this submartingale enable us to determine the running time of the algorithm.Abstract:
We analyze the performance of a Genetic Type Algorithm we call Culling and a variety of other algorithms on a problem we refer to as ASP. Culling is near optimal for this problem, highly noise tolerant, and the best known a~~roach . . in some regimes. We show that the problem of learning the Ising perception is reducible to noisy ASP. These results provide an example of a rigorous analysis of GA’s and give insight into when and how C,A’s can beat competing methods. To analyze the genetic algorithm, we view it as a special type of submartingale. We prove some new large deviation bounds on this submartingale w~ich enable us to determine the running time of the algorithm.read more
Citations
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Measuring and predicting adaptation in multidimensional activity-travel patterns
TL;DR: The final author version and the galley proof are versions of the publication after peer review that features the final layout of the paper including the volume, issue and page numbers.
Journal ArticleDOI
Constructive simulation of creative concept generation process in design: a research method for difficult-to-observe design-thinking processes
Toshiharu Taura,Eiko Yamamoto,Mohd Yusof Nor Fasiha,Masanori Goka,Futoshi Mukai,Yukari Nagai,Hideyuki Nakashima +6 more
TL;DR: The results suggest that thinking patterns in which explicit and ‘inexplicit’ concepts are continuously intertwined lead to creative design ideas.
Journal ArticleDOI
Empirical Modelling of Genetic Algorithms
Richard Myers,Edwin R. Hancock +1 more
TL;DR: This paper addresses the problem of reliably setting genetic algorithm parameters for consistent labelling problems by proposing a robust empirical framework, based on the analysis of factorial experiments, which are shown to be robust under extrapolation to up to triple the problem size.
Journal ArticleDOI
A comprehensive review of quadratic assignment problem: variants, hybrids and applications
TL;DR: QAP is NP-hard problem that is impossible to be solved in polynomial time when the problem size increases, hence heuristic and metaheuristic approaches are utilized for solving the problem instead of exact approaches because these approaches achieve quality in the solution in short computation time.
Journal ArticleDOI
Frpm artificial individuals to global patterns
TL;DR: Artificial Life simulations will be used not only to test ecological and evolutionary hypotheses explaining real organisms but also to show the validity of general theories, processes and concepts such as natural selection, theories of complexity, hierarchical relations and self-organization.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Book
Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Book ChapterDOI
Probability Inequalities for sums of Bounded Random Variables
TL;DR: In this article, upper bounds for the probability that the sum S of n independent random variables exceeds its mean ES by a positive number nt are derived for certain sums of dependent random variables such as U statistics.
Book
The Probabilistic Method
TL;DR: A particular set of problems - all dealing with “good” colorings of an underlying set of points relative to a given family of sets - is explored.