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    EC
    2007
    167views ECommerce» more  EC 2007»
    Comparison-Based Algorithms Are Robust and Randomized Algorithms Are Anytime
    13 years 5 months ago
    Comparison-Based Algorithms Are Robust and Randomized Algorithms Are Anytime
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    Randomized search heuristics (e.g., evolutionary algorithms, simulated annealing etc.) are very appealing to practitioners, they are easy to implement and usually provide good per...
    Sylvain Gelly, Sylvie Ruette, Olivier Teytaud
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    IPM
    2006
    78views more  IPM 2006»
    The effectiveness of Web search engines for retrieving relevant ecommerce links
    13 years 5 months ago
    The effectiveness of Web search engines for retrieving relevant ecommerce links
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    Ecommerce is developing into a fast-growing channel for new business, so a strong presence in this domain could prove essential to the success of numerous commercial organizations...
    Bernard J. Jansen, Paulo R. Molina
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    EXPERT
    2006
    75views more  EXPERT 2006»
    Customer-Driven Sensor Management
    13 years 5 months ago
    Customer-Driven Sensor Management
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    Customer-driven sensor management advocates bringing ecommerce concepts and advances to bear in sensor management. In ecommerce, customer wants essentially drive the production pr...
    Tracy Mullen, Viswanath Avasarala, David L. Hall
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    EC
    2006
    121views ECommerce» more  EC 2006»
    A Study of Structural and Parametric Learning in XCS
    13 years 5 months ago
    A Study of Structural and Parametric Learning in XCS
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    The performance of a learning classifier system is due to its two main components. First, it evolves new structures by generating new rules in a genetic process; second, it adjust...
    Tim Kovacs, Manfred Kerber
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    EC
    2006
    118views ECommerce» more  EC 2006»
    Human-Competitive Evolution of Quantum Computing Artefacts by Genetic Programming
    13 years 5 months ago
    Human-Competitive Evolution of Quantum Computing Artefacts by Genetic Programming
    Download  www-users.cs.york.ac.uk
    We show how Genetic Programming (GP) can be used to evolve useful quantum computing artefacts of increasing sophistication and usefulness: firstly specific quantum circuits, then ...
    Paul Massey, John A. Clark, Susan Stepney
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    EC
    2006
    153views ECommerce» more  EC 2006»
    GASAT: A Genetic Local Search Algorithm for the Satisfiability Problem
    13 years 5 months ago
    GASAT: A Genetic Local Search Algorithm for the Satisfiability Problem
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    This paper presents GASAT, a hybrid algorithm for the satisfiability problem (SAT). The main feature of GASAT is that it includes a recombination stage based on a specific crossov...
    Frédéric Lardeux, Frédé...
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    EC
    2006
    195views ECommerce» more  EC 2006»
    Automated Global Structure Extraction for Effective Local Building Block Processing in XCS
    13 years 5 months ago
    Automated Global Structure Extraction for Effective Local Building Block Processing in XCS
    Download  www.coboslab.psychologie.uni-wuerzburg.de
    Learning Classifier Systems (LCSs), such as the accuracy-based XCS, evolve distributed problem solutions represented by a population of rules. During evolution, features are speci...
    Martin V. Butz, Martin Pelikan, Xavier Llorà...
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    EC
    2006
    120views ECommerce» more  EC 2006»
    A Comparison of Bloat Control Methods for Genetic Programming
    13 years 5 months ago
    A Comparison of Bloat Control Methods for Genetic Programming
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    Genetic programming has highlighted the problem of bloat, the uncontrolled growth of the average size of an individual in the population. The most common approach to dealing with ...
    Sean Luke, Liviu Panait
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    EC
    2006
    136views ECommerce» more  EC 2006»
    Error Thresholds in Genetic Algorithms
    13 years 5 months ago
    Error Thresholds in Genetic Algorithms
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    The error threshold of replication is an important notion of the quasispecies evolution model; it is a critical mutation rate (error rate) beyond which structures obtained by an e...
    Gabriela Ochoa
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    EC
    2006
    97views ECommerce» more  EC 2006»
    A Step Forward in Studying the Compact Genetic Algorithm
    13 years 5 months ago
    A Step Forward in Studying the Compact Genetic Algorithm
    Download  www.public.iastate.edu
    The compact Genetic Algorithm (cGA) is an Estimation of Distribution Algorithm that generates offspring population according to the estimated probabilistic model of the parent pop...
    Reza Rastegar, Arash Hariri
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