Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)

16-19 July 2000

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  • Proceedings of the 2000 Congress on Evolutionary Computation

    Publication Year: 2000, Page(s):0_2 - xxvi
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    Freely Available from IEEE
  • Proceedings ASE 2000. Fifteenth IEEE International Conference on Automated Software Engineering

    Publication Year: 2000
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    Freely Available from IEEE
  • Author index

    Publication Year: 2000, Page(s):1585 - 1590
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    Freely Available from IEEE
  • On the genetic adaptation of stochastic learning automata

    Publication Year: 2000, Page(s):1079 - 1086 vol.2
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    Both stochastic learning automata and genetic algorithms have previously been shown to have valuable global optimisation properties. Learning automata have however been criticised for their perceived slow rate of convergence. In this paper these two techniques are combined to provide an increase in the rate of convergence for the learning automata and also to improve the escape from local minima. ... View full abstract»

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  • Agent based customer modelling: individuals who learn from their environment

    Publication Year: 2000, Page(s):1492 - 1497 vol.2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (432 KB)

    Understanding the rate of adoption of a telecommunications service in a population of customers is of prime importance to ensure that appropriate network capacity is provided to maintain quality of service. This problem goes beyond assessing the demand for a product based on usage and requires an understanding of how consumers learn about a service and evaluate its worth. Field studies have shown ... View full abstract»

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  • Generalisation and domain specific functions in genetic programming

    Publication Year: 2000, Page(s):1393 - 1400 vol.2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (684 KB)

    This research presents an evaluation of user defined domain specific functions of genetic programming using relational learning problems, generalisation for this class of learning problems and learning bias. After providing a brief theoretical background, two sets of experiments are detailed: experiments and results concerning the Monk-2 problem and experiments attempting to evolve generalising so... View full abstract»

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  • Dynamic rotation and partial visibility

    Publication Year: 2000, Page(s):1125 - 1131 vol.2
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (536 KB)

    This article generalizes a previously presented dynamic fitness function with two different concepts, namely a coordinate rotation and the concept of partial visibility. Those concepts define different classes of test problems. A set of standard evolution strategies and genetic algorithms with and without hypermutation are tested on two of the dynamic problem classes. They give insight into certai... View full abstract»

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  • Symmetry in the search space

    Publication Year: 2000, Page(s):1072 - 1078 vol.2
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (580 KB)

    The presence or symmetry in the representation of an optimization problem can have a positive or a negative influence on the dynamics of a search algorithm. Symmetry can cause a genetic algorithm or simulated annealing to get stuck in a local optimum, but it can also help an algorithm to find the optima more quickly, as the dual genetic algorithm does in some cases. The first part of the paper des... View full abstract»

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  • Assessing the performance of cultural algorithms for semantic network re-engineering

    Publication Year: 2000, Page(s):1482 - 1491 vol.2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (764 KB)

    Evolutionary computation has been successfully applied in a variety of problem domains and applications. The authors discuss the use of a specific form of evolutionary computation known as cultural algorithms to improve the efficiency of the subsumption algorithm in semantic networks. Subsumption is the process that determines if one node in the network is a child of another node. As such, it is u... View full abstract»

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  • Exploratory data modeling with Bayesian-driven evolutionary search

    Publication Year: 2000, Page(s):1385 - 1392 vol.2
    Cited by:  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (676 KB)

    We present a methodology for exploratory data modeling that combines evolutionary search with two levels of statistical inference provided by Bayesian interpolation (MacKay, 1992). Evolutionary methods are used to search in a space of model structures, whereas Bayesian interpolation is used to infer parameter values for candidate models as well as to evaluate the relative fitness of these models f... View full abstract»

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  • Emergent coordination for distributed information management

    Publication Year: 2000, Page(s):946 - 950 vol.2
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (376 KB)

    With an increase in the complexity of information systems, decentralised management techniques are becoming important. Such information systems will generally involve various computational and data nodes, managed by various organisations with differing policies and needs. Furthermore, in the absence of a centralised manager, co-ordination and interaction policies between such nodes become crucial.... View full abstract»

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  • MyEnglishTeacher-an evolutionary Web-based, multi-agent environment for academic English teaching

    Publication Year: 2000, Page(s):1345 - 1353 vol.2
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (752 KB)

    We describe our research on building a free, evolutionary, Internet-based, agent-based, long-distance teaching environment for academic English. Web English teaching environments are few, and mostly they imply a fee. However, none of them considers the challenges the non-native English-speaking academic has to face. We describe some of the design and implementation aspects of the system prototype,... View full abstract»

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  • Effects of hierarchical migration in a parallel distributed parameter-free GA

    Publication Year: 2000, Page(s):1117 - 1124 vol.2
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (604 KB)

    Effects of hierarchical migration methods in a parallel distributed Parameter-free GA (PfGA) are described. The PfGA is a compact and robust algorithm that extracts a local population from the whole population and evolves it by adaptively changing the size of the subpopulation. We propose hierarchically parallel distributed architectures with migration methods for the PfGA implementing them in a p... View full abstract»

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  • Solving constraint satisfaction problems with heuristic-based evolutionary algorithms

    Publication Year: 2000, Page(s):1571 - 1577 vol.2
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (568 KB)

    Evolutionary algorithms (EAs) for solving constraint satisfaction problems (CSPs) can be roughly divided into two classes: EAs with adaptive fitness functions and heuristic-based EAs. A.E. Eiben et al. (1998) compared effective EAs of the first class experimentally using a large set of benchmark instances consisting of randomly-generated binary CSPs. In this paper, we complete this comparison by p... View full abstract»

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  • Cultural algorithms in dynamic environments

    Publication Year: 2000, Page(s):1513 - 1520 vol.2
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (676 KB)

    Reasoning about environmental change in dynamic environments is a key factor in predicting an agent's next move in those environments. Cultural Algorithms provide a mechanism to reason about environmental dynamics. In this study, cultural algorithms show encouraging results when applied to environments where the problem is to find the highest peak in a multidimensional landscape, where the peaks a... View full abstract»

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  • Resolution of quadratic assignment problems using an evolutionary algorithm

    Publication Year: 2000, Page(s):902 - 909 vol.2
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (676 KB)

    This investigation presents evolution strategies to solve quadratic assignment problems. The proposed algorithm applies family competition and clustering to enhance the solution quality. Several problems obtained from QAPLIB (Burkard et al., 1991) were tested and experimental results were compared with other approaches in the literature. Experimental results also show that the proposed algorithm i... View full abstract»

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  • Experimental validations of the learnable evolution model

    Publication Year: 2000, Page(s):1064 - 1071 vol.2
    Cited by:  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (636 KB)

    A recently developed approach to evolutionary computation, called Learnable Evolution Model or LEM, employs machine learning to guide processes of generating new populations. The central new idea of LEM is that it generates new individuals not by mutation and/or recombination, but by processes of hypothesis generation and instantiation. The hypotheses are generated by a machine learning system fro... View full abstract»

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  • GP-based modeling method for time series prediction with parameter optimization and node alternation

    Publication Year: 2000, Page(s):1475 - 1481 vol.2
    Cited by:  Papers (3)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (456 KB)

    A fast method of GP based model building for time series prediction is proposed. The method involves two newly-devised techniques. One is regarding determination of model parameters: only functional forms are inherited from their parents with genetic programming, but model parameters are not inherited. They are optimized by a backpropagation-like algorithm when a child (model) is newborn. The othe... View full abstract»

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  • Genetic symbiosis algorithm

    Publication Year: 2000, Page(s):1377 - 1384 vol.2
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (612 KB)

    In this paper, a new genetic symbiosis algorithm (GSA) is proposed based on the symbiotic concept found widely in ecosystems. Since in the conventional genetic algorithms (GA) reproduction is done using only the fitness function of each individual, there are some problems such as premature convergence to an undesirable solution at a very early stage of generation. In addition in some GA applicatio... View full abstract»

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  • Convergence properties of incremental Bayesian evolutionary algorithms with single Markov chains

    Publication Year: 2000, Page(s):938 - 945 vol.2
    Cited by:  Papers (1)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (612 KB)

    Bayesian evolutionary algorithms (BEAs) are a probabilistic model of evolutionary computation for learning and optimization. Starting from a population of individuals drawn from a prior distribution, a Bayesian evolutionary algorithm iteratively generates a new population by estimating the posterior fitness distribution of parent individuals and then sampling from the distribution offspring indivi... View full abstract»

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  • A game-theoretic investigation of selection methods used in evolutionary algorithms

    Publication Year: 2000, Page(s):880 - 887 vol.2
    Cited by:  Papers (8)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (692 KB)

    The replicator equation used in evolutionary game theory (EGT) assumes that strategies reproduce in direct proportion to their payoffs; this is akin to the use of fitness-proportionate selection in an evolutionary algorithm (EA). In this paper, we investigate how various other selection methods commonly used in EAs can affect the discrete-time dynamics of EGT. In particular, we show that the exist... View full abstract»

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  • Evolutionary algorithm for multiresolutional conceptual learning

    Publication Year: 2000, Page(s):1337 - 1344 vol.2
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (656 KB)

    An effort is made to show how evolutionary algorithms (EA) can be applied within the domain of learning control systems with multiresolutional representation View full abstract»

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  • A new fitness function for discovering a lot of satisfiable solutions in constraint satisfaction problems

    Publication Year: 2000, Page(s):1184 - 1189 vol.2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (512 KB)

    In this paper, we discuss how many satisfiable solutions a genetic algorithm can find in a problem instance of a constraint satisfaction problems in a single execution. Hence, we propose a framework for a new fitness function which can be applied to traditional fitness functions. However, the mechanism of the proposed fitness function is quite simple, and several experimental results on a variety ... View full abstract»

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  • Evolutionary computation techniques for multiple sequence alignment

    Publication Year: 2000, Page(s):829 - 835 vol.2
    Cited by:  Papers (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (536 KB)

    Given a collection of biologically related protein or DNA sequences, the basic multiple sequence alignment problem is to determine the most biologically plausible alignment of these sequences. Under the assumption that the collection of sequences arose from some common ancestor, an alignment can be used to infer the evolutionary history among the sequences, i.e., the most likely pattern of inserti... View full abstract»

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  • Size of neighborhood more important than temperature for stochastic local search

    Publication Year: 2000, Page(s):1017 - 1024 vol.2
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (592 KB)

    We investigate stochastic local search by Markov chain analysis in a high and a low dimensional discrete space. In the n-dimensional space Bn a function called Jump is considered. The analysis shows that an algorithm using a large neighborhood and never accepting worse points performs much better than any local search algorithm accepting worse points with a certain probability. We also ... View full abstract»

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