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Machine learning --- Computer Science --- Engineering & Applied Sciences --- Computer science. --- Science. --- Computers. --- Mathematical logic. --- Artificial intelligence. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Science, general. --- Mathematical Logic and Formal Languages. --- Computation by Abstract Devices. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Calculators --- Cyberspace --- Natural science --- Science of science --- Sciences --- Informatics --- Science --- Artificial Intelligence. --- Science, Humanities and Social Sciences, multidisciplinary.
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The 5th International Workshop on Learning Classi?er Systems (IWLCS2002) was held September 7–8, 2002, in Granada, Spain, during the 7th International Conference on Parallel Problem Solving from Nature (PPSN VII). We have included in this volume revised and extended versions of the papers presented at the workshop. In the ?rst paper, Browne introduces a new model of learning classi?er system, iLCS, and tests it on the Wisconsin Breast Cancer classi?cation problem. Dixon et al. present an algorithm for reducing the solutions evolved by the classi?er system XCS, so as to produce a small set of readily understandable rules. Enee and Barbaroux take a close look at Pittsburgh-style classi?er systems, focusing on the multi-agent problem known as El-farol. Holmes and Bilker investigate the effect that various types of missing data have on the classi?cation performance of learning classi?er systems. The two papers by Kovacs deal with an important theoretical issue in learning classi?er systems: the use of accuracy-based ?tness as opposed to the more traditional strength-based ?tness. In the ?rst paper, Kovacs introduces a strength-based version of XCS, called SB-XCS. The original XCS and the new SB-XCS are compared in the second paper, where - vacs discusses the different classes of solutions that XCS and SB-XCS tend to evolve.
Machine learning --- Computer science. --- Computers. --- Mathematical logic. --- Database management. --- Artificial intelligence. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Computation by Abstract Devices. --- Mathematical Logic and Formal Languages. --- Database Management. --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Calculators --- Cyberspace --- Informatics --- Science --- Artificial Intelligence.
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Mathematical logic --- Computer science --- Artificial intelligence. Robotics. Simulation. Graphics --- informatica --- wiskunde --- KI (kunstmatige intelligentie) --- logica --- robots
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Mathematical logic --- Computer science --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- informatica --- database management --- wiskunde --- logica --- robots
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Models, Genetic --- Biological Evolution --- Mathematical Computing --- Genetic Processes --- Biological Processes --- Models, Biological --- Computing Methodologies --- Genetic Phenomena --- Models, Theoretical --- Information Science --- Biological Phenomena --- Investigative Techniques --- Phenomena and Processes --- Analytical, Diagnostic and Therapeutic Techniques and Equipment --- Computer Science --- Engineering & Applied Sciences --- Genetic programming (Computer science) --- Computer science. --- Software engineering. --- Computer programming. --- Computers. --- Algorithms. --- Artificial intelligence. --- Pattern recognition. --- Computer Science. --- Software Engineering/Programming and Operating Systems. --- Artificial Intelligence (incl. Robotics). --- Computation by Abstract Devices. --- Programming Techniques. --- Algorithm Analysis and Problem Complexity. --- Pattern Recognition. --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Algorism --- Algebra --- Arithmetic --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Cybernetics --- Calculators --- Cyberspace --- Computers --- Electronic computer programming --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Computer software engineering --- Engineering --- Informatics --- Science --- Foundations --- Programming --- Computer programming --- Genetic algorithms --- Computer software. --- Optical pattern recognition. --- Artificial Intelligence. --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Software, Computer
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The work embodied in this volume was presented across three consecutive e- tions of the International Workshop on Learning Classi?er Systems that took place in Chicago (2003), Seattle (2004), and Washington (2005). The Genetic and Evolutionary Computation Conference, the main ACM SIGEvo conference, hosted these three editions. The topics presented in this volume summarize the wide spectrum of interests of the Learning Classi?er Systems (LCS) community. The topics range from theoretical analysis of mechanisms to practical cons- eration for successful application of such techniques to everyday data-mining tasks. When we started editing this volume, we faced the choice of organizing the contents in a purely chronologicalfashion or as a sequence of related topics that help walk the reader across the di?erent areas. In the end we decided to or- nize the contents by area, breaking the time-line a little. This is not a simple endeavor as we can organize the material using multiple criteria. The tax- omy below is our humble e?ort to provide a coherent grouping. Needless to say, some works may fall in more than one category. The four areas are as follows: Knowledge representation. These chapters elaborate on the knowledge r- resentations used in LCS. Knowledge representation is a key issue in any learning system and has implications for what it is possible to learn and what mechanisms shouldbe used. Four chapters analyze di?erent knowledge representations and the LCS methods used to manipulate them.
Mathematical logic --- Computer science --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- informatica --- database management --- wiskunde --- logica --- robots
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The two volume set LNCS 3102/3103 constitutes the refereed proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2004, held in Seattle, WA, USA, in June 2004. The 230 revised full papers and 104 poster papers presented were carefully reviewed and selected from 460 submissions. The papers are organized in topical sections on artificial life, adaptive behavior, agents, and ant colony optimization; artificial immune systems, biological applications; coevolution; evolutionary robotics; evolution strategies and evolutionary programming; evolvable hardware; genetic algorithms; genetic programming; learning classifier systems; real world applications; and search-based software engineering.
Genetic algorithms --- Parallel processing (Electronic computers) --- Data processing --- Evolutionary computation. --- Genetic computation. --- GAs (Algorithms) --- Genetic searches (Algorithms) --- Computer science. --- Microprocessors. --- Computers. --- Algorithms. --- Computer science --- Artificial intelligence. --- Bioinformatics. --- Computer Science. --- Computation by Abstract Devices. --- Algorithm Analysis and Problem Complexity. --- Artificial Intelligence (incl. Robotics). --- Processor Architectures. --- Discrete Mathematics in Computer Science. --- Mathematics. --- Computer Science, general. --- Algorithms --- Combinatorial optimization --- Evolutionary computation --- Genetic programming (Computer science) --- Learning classifier systems --- Computer software. --- Computational complexity. --- Artificial Intelligence. --- Bio-informatics --- Biological informatics --- Biology --- Information science --- Computational biology --- Systems biology --- Complexity, Computational --- Electronic data processing --- Machine theory --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Software, Computer --- Computer systems --- Informatics --- Science --- Computer science—Mathematics. --- Minicomputers --- Algorism --- Algebra --- Arithmetic --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Cybernetics --- Calculators --- Cyberspace --- Foundations --- Genetic algorithms - Data processing - Congresses --- Parallel processing (Electronic computers) - Congresses
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