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The Cooperative Coevolutionary (1+1) EA

Thomas Jansen, R. Paul Wiegand
2004 Evolutionary Computation  
Using the cooperative coevolutionary framework as a starting point, the CC (1+1) EA is defined and investigated. The main interest is in the analysis of the expected optimization time.  ...  It is shown that separability alone is not sufficient to yield any advantage of the CC (1+1) EA over its traditional, non-coevolutionary counterpart.  ...  We use the (1+1) EA as the underlying search heuristic and obtain a cooperative coevolutionary (1+1) EA.  ... 
doi:10.1162/1063656043138905 pmid:15768523 fatcat:baifdzzjprdobja2p7qzo64zdy

Exploring the Explorative Advantage of the Cooperative Coevolutionary (1+1) EA [chapter]

Thomas Jansen, R. Paul Wiegand
2003 Lecture Notes in Computer Science  
Using a well-known cooperative coevolutionary function optimization framework, a very simple cooperative coevolutionary (1+1) EA is defined.  ...  Therefore, a systematic comparison between the expected optimization times of this coevolutionary algorithm and the ordinary (1+1) EA is presented.  ...  The research was partly conducted during a visit to George Mason University. This was supported by a fellowship within the post-doctoral program of the German Academic Exchange Service (DAAD).  ... 
doi:10.1007/3-540-45105-6_37 fatcat:jci2kh74ind2tbfja3oi75z7ru

A cooperative coevolutionary algorithm for the Multi-Depot Vehicle Routing Problem

Fernando Bernardes de Oliveira, Rasul Enayatifar, Hossein Javedani Sadaei, Frederico Gadelha Guimarães, Jean-Yves Potvin
2016 Expert systems with applications  
This paper introduces a cooperative coevolutionary algorithm to minimize the total route cost of the MDVRP.  ...  Coevolutionary algorithms are inspired by the simultaneous evolution process involving two or more species.  ...  Javedani Sadaei would like to thank the support given by the Brazilian Agency CAPES. F. G.  ... 
doi:10.1016/j.eswa.2015.08.030 fatcat:5a467kehrjd55en2zzwingln6m

Multipopulation cooperative coevolutionary programming (MCCP) to enhance design innovation

Emily M. Zechman, S. Ranji Ranjithan
2005 Proceedings of the 2005 conference on Genetic and evolutionary computation - GECCO '05  
This paper describes the development of an evolutionary algorithm called Multipopulation Cooperative Coevolutionary Programming (MCCP) that extends Genetic Programming (GP) to search for a set of maximally  ...  The GP search is structured to generate a set of alternatives that are similar in design performance, but are dissimilar from each other in the solution (or design parameter) space.  ...  The viewpoints presented here are those of the authors and do not necessarily reflect those of the funding agencies.  ... 
doi:10.1145/1068009.1068286 dblp:conf/gecco/ZechmanR05 fatcat:ofhq7rnro5dv5cpqdupq44bqe4

Archive-based cooperative coevolutionary algorithms

Liviu Panait, Sean Luke, Joseph F. Harrison
2006 Proceedings of the 8th annual conference on Genetic and evolutionary computation - GECCO '06  
Archive-based cooperative coevolutionary algorithms attempt to retain a set of individuals which act as good collaborators for other coevolved individuals in the evolutionary system.  ...  We introduce a new archive-based algorithm, called iCCEA, which compares favorably with other cooperative coevolutionary algorithms.  ...  One notional use of cooperative coevolutionary algorithms (CCEAs) is to take advantage of decomposable problems to simplify the search space.  ... 
doi:10.1145/1143997.1144060 dblp:conf/gecco/PanaitLH06 fatcat:a5oyfxeadzdkfdxejhmcckdwk4

A cooperative coevolutionary approach dealing with the skull–face overlay uncertainty in forensic identification by craniofacial superimposition

O. Ibáñez, O. Cordón, S. Damas
2011 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
In this paper, we propose a novel approach, a cooperative coevolutionary algorithm, to deal with the use of imprecise cephalometric landmarks in the skull-face overlay process, the main task in craniofacial  ...  Coevolutionary skull-face overlay results are compared with our previous fuzzy-evolutionary automatic method.  ...  We would like to acknowledge all the team of the Physical Anthropology Lab at the University of Granada (headed by Dr. Botella and Dr.  ... 
doi:10.1007/s00500-011-0770-8 fatcat:37feonbzancv7lea7ytnab6q44

Using Compact Coevolutionary Algorithm for Matching Biomedical Ontologies

Xingsi Xue, Jie Chen, Junfeng Chen, Dongxu Chen
2018 Computational Intelligence and Neuroscience  
To overcome these shortcomings, we propose a compact CoEvolutionary Algorithm to efficiently match the biomedical ontologies.  ...  Although Evolutionary algorithms (EAs) are one of the state-of-the-art methodologies to match the heterogeneous ontologies, huge memory consumption, long runtime, and the bias improvement of the solutions  ...  the cooperative coevolving process.  ... 
doi:10.1155/2018/2309587 pmid:30405706 pmcid:PMC6199880 fatcat:3banmvgle5gzhputmvdd3tgfee

CoBRA: A cooperative coevolutionary algorithm for bi-level optimization

Francois Legillon, Arnaud Liefooghe, El-Ghazali Talbi
2012 2012 IEEE Congress on Evolutionary Computation  
It handles population-based algorithms on each level, each one cooperating with the other to provide solutions for the overall problem.  ...  This article presents CoBRA, a new evolutionary algorithm, based on a coevolutionary scheme, to solve bi-level optimization problems.  ...  COBRA, A COOPERATIVE COEVOLUTIONARY ALGORITHM FOR BI-LEVEL OPTIMIZATION In this section we introduce CoBRA, a new EA to tackle bi-level optimization problems.  ... 
doi:10.1109/cec.2012.6256620 dblp:conf/cec/LegillonLT12 fatcat:r6b4m3fi6rapxpa55zdotcfz2y

Reference sharing: a new collaboration model for cooperative coevolution

Min Shi, Shang Gao
2017 Journal of Heuristics  
Cooperative coevolutionary algorithms have been a popular and effective learning approach to solve optimization problems through problem decomposition.  ...  Furthermore, we demonstrate and analyze our algorithm through comparison studies with other popular cooperative coevolutionary models on a suite of standard function optimization problems.  ...  , and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1007/s10732-016-9322-9 fatcat:57azwyabqbg2pa3m7mjb4xv7gy

Relationship Between Generalization and Diversity in Coevolutionary Learning

Siang Yew Chong, P. Tino, Xin Yao
2009 IEEE Transactions on Computational Intelligence and AI in Games  
Games have long played an important role in the development and understanding of coevolutionary learning systems.  ...  In particular, the search process in coevolutionary learning is guided by strategic interactions between solutions in the population, which can be naturally framed as game playing.  ...  computing support in running the experiments.  ... 
doi:10.1109/tciaig.2009.2034269 fatcat:loqpbdo76zarxm6mvpr6wbc6n4

A Parallel Multi-Objective Cooperative Coevolutionary Algorithm for Optimising Small-World Properties in VANETs

Grégoire Danoy, Julien Schleich, Pascal Bouvry, Bernabé Dorronsoro
2014 CLEI Electronic Journal  
This article proposes to apply for the first time a state-of-the-art parallel asynchronous cooperative coevolutionary variant of the non- dominated sorting genetic algorithm II (NSGA-II), named CCNSGA-II  ...  Cooperative coevolutionary evolutionary algorithms differ from standard evolutionary algorithms' architecture in that the population is split into subpopulations, each of them optimising only a sub-vector  ...  Dorronsoro acknowledges the support offered by the National Research Fund, Luxembourg, AFR contract no 4017742.  ... 
doi:10.19153/cleiej.17.1.1 fatcat:xbdsy4yhivaldpelyrsgwrp5oe

Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents

Mitchell A. Potter, Kenneth A. De Jong
2000 Evolutionary Computation  
In this paper, we describe an architecture for evolving such subcomponents as a collection of cooperating species.  ...  Given a simple stringmatching task, we show that evolutionary pressure to increase the overall fitness of the ecosystem can provide the needed stimulus for the emergence of an appropriate number of interdependent  ...  Acknowledgments This work was supported by the Office of Naval Research.  ... 
doi:10.1162/106365600568086 pmid:10753229 fatcat:vetoyo7vuzdpdnslquk5q6dgr4

A cooperative coevolutionary algorithm with Correlation based Adaptive Variable Partitioning

Tapabrata Ray, Xin Yao
2009 2009 IEEE Congress on Evolutionary Computation  
A cooperative coevolutionary algorithm (CCEA) is an extension to an evolutionary algorithm (EA); it employs a divide and conquer strategy to solve an optimization problem.  ...  The performance of CCEA-AVP is compared with CCEA and EA to highlight its benefits.  ...  2] , which has since then been referred as cooperative coevolutionary algorithm (CCEA).  ... 
doi:10.1109/cec.2009.4983052 dblp:conf/cec/RayY09 fatcat:stq373ivkrhfbox6vm2hf4tctm

The Evolved Apprentice Model: Scope and Limits

Kim Sterelny
2013 Biological Theory  
Downes, Gerrans, and Sutton all raise important issues for the account of human social learning and cooperation developed in The Evolved Apprentice.  ...  Gerrans probes the model on the relationship between social learning and imitation; I respond by arguing that imitation became important relatively late in the human social learning career, probably via  ...  One is an important aspect of the coevolutionary picture: the role of hunting.  ... 
doi:10.1007/s13752-013-0098-y fatcat:twvg6oamvfablmavxucgvhs5me

Analyzing Oligopolistic Electricity Market Using Coevolutionary Computation

H. Chen, K.P. Wong, D.H.M. Nguyen, C.Y. Chung
2006 IEEE Transactions on Power Systems  
This paper presents a new unified framework of electricity market analysis based on coevolutionary computation (CCEM) for both the one-shot and the repeated games of oligopolistic electricity markets.  ...  The standard Cournot model and the new Pareto improvement model are used. The linear and constant elasticity demand functions are considered.  ...  Each species is evolved through the repeated application of a conventional EA. Fig. 2 shows the fitness evaluation phase of the EA from the perspective of species 1.  ... 
doi:10.1109/tpwrs.2005.862005 fatcat:otxpcrpfvjbajhwsg6q3invhuq
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