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 David E Goldberg

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Average citations per article60.84
Citation Count11,560
Publication count190
Publication years1985-2012
Available for download100
Average downloads per article158.03
Downloads (cumulative)15,803
Downloads (12 Months)728
Downloads (6 Weeks)98
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182 results found Export Results: bibtexendnoteacmrefcsv

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1
March 2012 Theoretical Computer Science: Volume 425, March, 2012
Publisher: Elsevier Science Publishers Ltd.
Bibliometrics:
Citation Count: 8

It has been shown many times that the evolutionary online learning XCS classifier system is a robustly generalizing reinforcement learning system, which also yields highly competitive results in data mining applications. The XCSF version of the system is a real-valued function approximation system, which learns piecewise overlapping local linear models ...
Keywords: Resource management, Function approximation, Learning classifier system, Scalability, Structure alignment, XCS

2
March 2012 Evolutionary Computation: Volume 20 Issue 1, Spring 2012
Publisher: MIT Press
Bibliometrics:
Citation Count: 4
Downloads (6 Weeks): 1,   Downloads (12 Months): 3,   Downloads (Overall): 81

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Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that explore the space of potential solutions by building and sampling explicit probabilistic models of promising candidate solutions. While the primary goal of applying EDAs is to discover the global optimum or at least its accurate approximation, besides this, any EDA ...
Keywords: estimation of distribution algorithms, efficiency enhancement, learning from experience, model complexity, Hierarchical BOA, model structure, probabilistic model

3
July 2011 Soft Computing - A Fusion of Foundations, Methodologies and Applications: Volume 15 Issue 7, July 2011
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 4

Evolutionary algorithms (EAs) are particularly suited to solve problems for which there is not much information available. From this standpoint, estimation of distribution algorithms (EDAs), which guide the search by using probabilistic models of the population, have brought a new view to evolutionary computation. While solving a given problem with ...
Keywords: Bayesian networks, Bayesian optimization algorithm, Estimation of distribution algorithms, Model overfitting, Selection

4 published by ACM
July 2010 GECCO '10: Proceedings of the 12th annual conference on Genetic and evolutionary computation
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 0,   Downloads (12 Months): 3,   Downloads (Overall): 95

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Michigan-style learning classifier systems solve problems by evolving distributed subsolutions online. Extracting accurate models for subsolutions which are represented by a low number of examples in the training data set has been identified as a key challenge in LCS, and facetwise analysis has been applied to identify the critical elements ...
Keywords: genetic-based machine learning, learning classifier systems, small disjuncts, class imbalance problem

5
December 2009 Evolutionary Computation: Volume 17 Issue 4, Winter 2009
Publisher: MIT Press
Bibliometrics:
Citation Count: 19
Downloads (6 Weeks): 1,   Downloads (12 Months): 19,   Downloads (Overall): 464

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In many different fields, researchers are often confronted by problems arising from complex systems. Simple heuristics or even enumeration works quite well on small and easy problems; however, to efficiently solve large and difficult problems, proper decomposition is the key. In this paper, investigating and analyzing interactions between components of ...
Keywords: modularity, problem decomposition, Genetic algorithms, dependency structure matrix, overlap, hierarchy

6
November 2009 ISDA '09: Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 31

Genetic algorithms(GAs) are increasingly being applied to large scale problems. The traditional MPI-based parallel GAs require detailed knowledge about machine architecture. On the other hand, MapReduce is a powerful abstraction proposed by Google for making scalable and fault tolerant applications. In this paper, we show how genetic algorithms can be ...
Keywords: Genetic Algorithms, MapReduce, Scalability

7
November 2009 ISDA '09: Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 0

One of the main problems that arises when using gene expression programming (GEP) conditions in learning classifier systems is the increasing number of symbols present as the problem size grows. When doing model-building LCS, this issue limits the scalability of such a technique, due to the cost required. This paper ...
Keywords: machine learning, genetic algorithms, gene expression programming, classifier systems

8
October 2009 IEEE Transactions on Evolutionary Computation: Volume 13 Issue 5, October 2009
Publisher: IEEE Press
Bibliometrics:
Citation Count: 20

Michigan-style learning classifier systems (LCSs) are online machine learning techniques that incrementally evolve distributed subsolutions which individually solve a portion of the problem space. As in many machine learning systems, extracting accurate models from problems with class imbalances--that is, problems in which one of the classes is poorly represented with ...
Keywords: Class imbalance problem, genetic algorithms, learning classifier systems, class imbalance problem, facetwise modeling, patchquilt integration

9
September 2009 SLS '09: Proceedings of the Second International Workshop on Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 8

This paper presents a local search method for the Bayesian optimization algorithm (BOA) based on the concepts of substructural neighborhoods and loopy belief propagation. The probabilistic model of BOA, which automatically identifies important problem substructures, is used to define the topology of the neighborhoods explored in local search. On the ...

10 published by ACM
July 2009 GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 1,   Downloads (12 Months): 3,   Downloads (Overall): 115

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Many successful applications have proven the potential of Learning Classifier Systems and the XCS classifier system in particular in datamining, reinforcement learning, and function approximation tasks. Recent research has shown that XCS is a highly flexible system, which can be adapted to the task at hand by adjusting its condition ...
Keywords: function approximation, learning classifier systems, lwpr, recursive least squares, xcs

11 published by ACM
July 2009 GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Publisher: ACM
Bibliometrics:
Citation Count: 2
Downloads (6 Weeks): 0,   Downloads (12 Months): 2,   Downloads (Overall): 147

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Learning Classifier Systems (LCSs) are rule-based systems that can be manipulated by a genetic algorithm. LCSs were first designed by Holland to solve classification problems and a lot of effort has been made since then, resulting in a broad number of different algorithms. One of these is called Organizational Classifier ...
Keywords: ga, lcs, multi-label classification, ocs

12 published by ACM
July 2009 GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Publisher: ACM
Bibliometrics:
Citation Count: 21
Downloads (6 Weeks): 2,   Downloads (12 Months): 5,   Downloads (Overall): 173

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This paper presents a class of NK landscapes with nearest-neighbor interactions and tunable overlap. The considered class of NK landscapes is solvable in polynomial time using dynamic programming; this allows us to generate a large number of random problem instances with known optima. Several genetic and evolutionary algorithms are then ...
Keywords: crossover, fitness landscape, genetic algorithm, hboa, hierarchical boa, hybridization, nk fitness landscape, performance analysis, problem difficulty, scalability

13 published by ACM
July 2009 GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Publisher: ACM
Bibliometrics:
Citation Count: 6
Downloads (6 Weeks): 1,   Downloads (12 Months): 4,   Downloads (Overall): 154

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The ECGA is a competent Genetic Algorithm that uses a probabilistic model to learn the linkage among variables and then uses this information to solve hard problems using polynomial resources. However, in order to detect the linkage, the ECGA needs to perform a quadratic number of evaluations of a metric ...
Keywords: DSMGA, ECGA, efficiency enhancement, estimation of distribution algorithms, model building

14 published by ACM
July 2009 GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 0,   Downloads (12 Months): 3,   Downloads (Overall): 124

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One of the main problems that arises when using gene expression programming (GEP) conditions in learning classifier systems is the increasing number of symbols present as the problem size grows. When doing model-building LCS, this issue limits the scalability of such a technique, due to the cost required. This paper ...
Keywords: classifier systems, gene expression programming, genetic algorithms, machine learning

15 published by ACM
July 2009 GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Publisher: ACM
Bibliometrics:
Citation Count: 3
Downloads (6 Weeks): 0,   Downloads (12 Months): 1,   Downloads (Overall): 109

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Hybridization of global and local search algorithms is a well-established technique for enhancing the efficiency of search algorithms. Hybridizing estimation of distribution algorithms (EDAs) has been repeatedly shown to produce better performance than either the global or local search algorithm alone. The hierarchical Bayesian optimization algorithm (hBOA) is an advanced ...
Keywords: efficiency enhancement, estimation of distribution algorithms, hierarchical boa, hybrid evolutionary algorithms, local search, maxsat, spin glass, trap-5

16
December 2008 ESCIENCE '08: Proceedings of the 2008 Fourth IEEE International Conference on eScience
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 19

Data-intensive flow computing allows efficient processing of large volumes of data otherwise unapproachable. This paper introduces a new semantic-driven data-intensive flow infrastructure which: (1) provides a robust and transparent scalable solution from a laptop to large-scale clusters,(2) creates an unified solution for batch and interactive tasks in high-performance computing environments, ...

17
October 2008 Learning Classifier Systems: 10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006 and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007, Revised Selected Papers
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 2

This paper reviews a <em>competent</em>Pittsburgh LCS that automatically <em>mines</em>important substructures of the underlying problems and takes problems that were <em>intractable</em>with first-generation Pittsburgh LCS and renders them <em>tractable</em>. Specifically, we propose a <em>?</em>-ary extended compact classifier system (<em>?</em>eCCS) which uses (1) a competent genetic algorithm (GA) in the form of <em>?</em>-ary ...

18
October 2008 Learning Classifier Systems: 10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006 and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007, Revised Selected Papers
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 3

This paper presents a learning methodology based on a substructural classification model to solve decomposable classification problems. The proposed method consists of three important components: (1) a structural model, which represents salient interactions between attributes for a given data, (2) a surrogate model, which provides a functional approximation of the ...

19
September 2008 Proceedings of the 10th International Conference on Parallel Problem Solving from Nature --- PPSN X - Volume 5199
Publisher: Springer-Verlag New York, Inc.
Bibliometrics:
Citation Count: 8

In this paper we show preliminary results of two efficiency enhancements proposed for Extended Compact Genetic Algorithm. First, a model building enhancement was used to reduce the complexity of the process from O n 3 to O n 2 , speeding up the algorithm by 1000 times on a 4096 ...
Keywords: Efficiency Enhancement, Estimation of Distribution Algorithms, ECGA, Model Building

20
September 2008 Evolutionary Computation: Volume 16 Issue 3, Fall 2008
Publisher: MIT Press
Bibliometrics:
Citation Count: 19
Downloads (6 Weeks): 4,   Downloads (12 Months): 23,   Downloads (Overall): 723

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A wide range of niching techniques have been investigated in evolutionary and genetic algorithms. In this article, we focus on niching using crowding techniques in the context of what we call local tournament algorithms. In addition to deterministic and probabilistic crowding, the family of local tournament algorithms includes the Metropolis ...
Keywords: niching, portfolios, population sizing, Genetic algorithms, deterministic crowding, probabilistic crowding, crowding, local tournaments



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