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Showing 1 to 6 of 6 for “"Learning Classifier Systems"”.

  1. Architecture design and simulation for distributed learning classifier systems

    In this thesis, we introduce the Distributed Learning Classifier System (DLCS) as a novel extension of J. H. Holland's standard learning classifier system. While the standard LCS offers effective real-time control and learning, one of its limitations is that it does not provide a mechanism for …

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  2. A Radial Basis Function Approach to a Color Image Classification Problem in a Real Time Industrial Application

    … also examined in this work. The minimum distance classifiers are presented since they have been employed by the previous research. We give brief definitions about color space, color texture, color quantization, color classification methods. We also give an intensive review of radial basis …

    vt Repository record for A Radial Basis Function Approach to a Color Image Classification Problem in a Real Time Industrial Application (opens in a new tab)

  3. Evolutionary environmental modelling in self-managing software systems

    … richness and sophistication of modem software systems has challenged conventional design-time software modelling analysis and has led to a number of studies exploring non-conventional approaches particularly those inspired by nature. The natural world routinely produces organisms that can not …

    liverpool-jm Repository record for Evolutionary environmental modelling in self-managing software systems (opens in a new tab)

  4. Rule -Based Evolutionary Online Learning Systems: Learning Bounds, Classification, and Prediction

    Rule-based evolutionary online learning systems, often referred to as Michigan-style learning classifier systems (LCSs), were proposed nearly thirty years ago (Holland, 1976; Holland, 1977) originally calling them cognitive systems. LCSs combine the strength of reinforcement learning with the …

    uiuc Repository record for Rule -Based Evolutionary Online Learning Systems: Learning Bounds, Classification, and Prediction (opens in a new tab)

  5. A Distributed Q-learning Classifier System for task decomposition in real robot learning problems

    A distributed reinforcement-learning system is designed and implemented on a mobile robot for the study of complex task decomposition in real robot learning environments. The Distributed Q-learning Classifier System (DQLCS) is evolved from the standard Learning Classifier System (LCS) proposed by …

    vt Repository record for A Distributed Q-learning Classifier System for task decomposition in real robot learning problems (opens in a new tab)