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Evolutionary algorithms in theory and practice
TLDR
In this work, the author compares the three most prominent representatives of evolutionary algorithms: genetic algorithms, evolution strategies, and evolutionary programming within a unified framework, thereby clarifying the similarities and differences of these methods.About:
The article was published on 1996-01-01 and is currently open access. It has received 2679 citations till now. The article focuses on the topics: Evolutionary music & Evolutionary programming.read more
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Journal ArticleDOI
Connecting a connectome to behavior: an ensemble of neuroanatomical models of C. elegans klinotaxis.
TL;DR: This paper develops a neuroanatomically-grounded model of salt klinotaxis, a form of chemotaxis in which changes in orientation are directed towards the source through gradual continual adjustments.
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Empirical Review of Standard Benchmark Functions Using Evolutionary Global Optimization
TL;DR: In this paper, a recent implementation of genetic algorithms is used to study a range of standard benchmark functions for global optimization, and it turns out that some of them are not very useful as challenging test functions, since they neither allow for a discrimination between different variants of genetic operators nor exhibit a dimensionality scaling resembling that of real-world problems, for example that of global structure optimization of atomic and molecular clusters.
Journal ArticleDOI
Selecting the most efficient genetic algorithm sets in solving unconstrained building optimization problem
Ali Alajmi,Jonathan A. Wright +1 more
TL;DR: The results show that population size is the most significant control parameter and that the crossover probability and mutation rate have insignificant effects on the GA performance.
Proceedings ArticleDOI
Optimal sampling strategies for learning a fitness model
TL;DR: The paper investigates the use of kriging interpolation and estimation as a function approximation tool for the optimization of computationally complex functions.
Journal ArticleDOI
Multi-Issue Negotiation Processes by Evolutionary Simulation, Validationand Social Extensions
TL;DR: In this paper, the authors describe a system for bilateral negotiations in which artificial agents are generated by an EA and the negotiations are governed by a finite-horizon version of the alternating-offers protocol.