Works matching DE "LEARNING classifier systems"
Results: 204
Learning to Play Using Low-Complexity Rule-Based Policies: Illustrations through Ms. Pac-Man.
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- Journal of Artificial Intelligence Research, 2007, v. 30, p. 659, doi. 10.1613/jair.2368
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iMem-Seq: A Multi-label Learning Classifier for Predicting Membrane Proteins Types.
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- Journal of Membrane Biology, 2015, v. 248, n. 4, p. 745, doi. 10.1007/s00232-015-9787-8
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Optimization of concrete shells using genetic algorithms.
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- ZAMM -- Journal of Applied Mathematics & Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 2014, v. 94, n. 1/2, p. 43, doi. 10.1002/zamm.201200215
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Escala. Perturbaciones escalares.
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- Revista de Filosofía (0185-3481), 2019, v. 51, n. 146, p. 18
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A Method of Partner Selection for Knowledge Collaboration Teams using Weighted Social Network Analysis.
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- Journal of Intelligent Systems, 2018, v. 27, n. 4, p. 577, doi. 10.1515/jisys-2016-0140
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Generating Tree-Level Harvest Predictions from Forest Inventories with Random Forests.
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- Forests (19994907), 2019, v. 10, n. 1, p. 20, doi. 10.3390/f10010020
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A Coordinated Air Defense Learning System Based on Immunized Classifier Systems.
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- Symmetry (20738994), 2021, v. 13, n. 2, p. 271, doi. 10.3390/sym13020271
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Taxon selection using statistical learning techniques to improve transfer function prediction.
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- Holocene, 2015, v. 25, n. 1, p. 130, doi. 10.1177/0959683614556388
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'Proactive' use of cue-context congruence for building reinforcement learning's reward function.
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- BMC Neuroscience, 2016, v. 17, p. 1, doi. 10.1186/s12868-016-0302-7
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Predicting disease risks from highly imbalanced data using random forest.
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- BMC Medical Informatics & Decision Making, 2011, v. 11, n. 1, p. 51, doi. 10.1186/1472-6947-11-51
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- Article
Sigma-RF: prediction of the variability of spatial restraints in template-based modeling by random forest.
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- BMC Bioinformatics, 2015, v. 16, n. 1, p. 1, doi. 10.1186/s12859-015-0526-z
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Robustness of Random Forest-based gene selection methods.
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- BMC Bioinformatics, 2014, v. 15, n. 1, p. 2, doi. 10.1186/1471-2105-15-8
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A comparison of methods to calculate a total merit index using stochastic simulation.
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- Genetics Selection Evolution, 2015, v. 47, n. 1, p. 1, doi. 10.1186/s12711-015-0118-4
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Sequence- vs. chip-assisted genomic selection: accurate biological information is advised.
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- Genetics Selection Evolution, 2015, v. 47, n. 1, p. 1, doi. 10.1186/s12711-015-0117-5
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Optimization of genomic selection training populations with a genetic algorithm.
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- Genetics Selection Evolution, 2015, v. 47, n. 1, p. 1, doi. 10.1186/s12711-015-0116-6
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A Meta-ensemble Predictive Model for the Risk of Lung Cancer.
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- Al-Bahir Journal for Engineering & Pure Sciences, 2024, v. 5, n. 1, p. 52, doi. 10.55810/2313-0083.1068
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Joint relay and channel selection against mobile and smart jammer: A deep reinforcement learning approach.
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- IET Communications (Wiley-Blackwell), 2021, v. 15, n. 17, p. 2237, doi. 10.1049/cmu2.12257
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Towards Realizing Intelligent Coordinated Controllers for Multi-USV Systems Using Abstract Training Environments.
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- Journal of Marine Science & Engineering, 2021, v. 9, n. 6, p. 560, doi. 10.3390/jmse9060560
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Recognition of human activities using a multiclass relevance vector machine.
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- Optical Engineering, 2012, v. 51, n. 1, p. 017202-1, doi. 10.1117/1.OE.51.1.017202
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GA-Based Keyword Selection for the Design of an Intelligent Web Document Search System.
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- Computer Journal, 2009, v. 52, n. 8, p. 890, doi. 10.1093/comjnl/bxn049
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Improving the efficiency of the XCS learning classifier system using evolutionary memory.
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- Wireless Networks (10220038), 2024, v. 30, n. 6, p. 5171, doi. 10.1007/s11276-023-03228-5
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Editorial.
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- ISeCure, 2018, v. 10, n. 2, p. 77
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GACO - A HYBRID ANT COLONY OPTIMIZATION METAHEURISTIC FOR THE DYNAMIC LOAD-BALANCED CLUSTERING PROBLEM IN AD HOC NETWORKS.
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- Applied Artificial Intelligence, 2009, v. 23, n. 7, p. 570, doi. 10.1080/08839510903161139
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A Supervised Manifold Learning Method.
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- Computer Science & Information Systems, 2009, v. 6, n. 2, p. 205, doi. 10.2298/csis0902205L
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Automatic Discovery and Transfer of Task Hierarchies in Reinforcement Learning.
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- AI Magazine, 2011, v. 32, n. 1, p. 35, doi. 10.1609/aimag.v32i1.2342
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An Introduction to Intertask Transfer for Reinforcement Learning.
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- AI Magazine, 2011, v. 32, n. 1, p. 15, doi. 10.1609/aimag.v32i1.2329
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Adaptive Educational Software by Applying Reinforcement Learning.
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- Informatics in Education, 2013, v. 12, n. 1, p. 13, doi. 10.15388/infedu.2013.02
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Predicting Software Defects for Object-Oriented Software Using Search-based Techniques.
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- International Journal of Software Engineering & Knowledge Engineering, 2021, v. 31, n. 2, p. 193, doi. 10.1142/S0218194021500054
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Distributed Brain Networks Reflect Salary Offer in Accordance With the Prospect Theory's Value Function.
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- Journal of Neuroscience, Psychology, & Economics, 2017, v. 10, n. 4, p. 167, doi. 10.1037/npe0000083
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Asynchronous cellular automata and pattern classification.
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- Complexity, 2016, v. 21, p. 370, doi. 10.1002/cplx.21749
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Visualizations for rule-based machine learning.
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- Natural Computing, 2022, v. 21, n. 2, p. 243, doi. 10.1007/s11047-020-09840-0
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An adaptive genetic algorithm for parameter estimation of biological oscillator models to achieve target quantitative system response.
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- Natural Computing, 2014, v. 13, n. 1, p. 119, doi. 10.1007/s11047-013-9383-8
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Modelling the nonlinear dynamic behaviour of a boiler-turbine system using a radial basis function neural network.
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- International Journal of Robust & Nonlinear Control, 2014, v. 24, n. 13, p. 1873, doi. 10.1002/rnc.2969
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Multi-objective optimal design of hybrid viscoelastic/composite sandwich beams by using the generalized differential quadrature method and the non-dominated sorting genetic algorithm II.
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- Structural & Multidisciplinary Optimization, 2017, v. 56, n. 4, p. 885, doi. 10.1007/s00158-017-1695-3
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Combining genetic algorithms with BESO for topology optimization.
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- Structural & Multidisciplinary Optimization, 2009, v. 38, n. 5, p. 511, doi. 10.1007/s00158-008-0297-5
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Multiobjective Optimal Design of Sewerage Rehabilitation by Using the Nondominated Sorting Genetic Algorithm-II.
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- Water Resources Management, 2016, v. 30, n. 2, p. 487, doi. 10.1007/s11269-015-1173-x
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Two-Step Markov Update Algorithm for Accuracy-Based Learning Classifier Systems.
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- Complex Systems, 2018, v. 27, n. 1, p. 63, doi. 10.25088/complexsystems.27.1.63
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Non-parametric Policy Search with Limited Information Loss.
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- Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1
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A distributed block coordinate descent method for training l<sub>1</sub> regularized linear classifiers.
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- Journal of Machine Learning Research, 2017, v. 18, n. 64-98, p. 1
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On the Foundations of Noise-free Selective Classification.
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- Journal of Machine Learning Research, 2010, v. 11, n. 5, p. 1605
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Transfer Learning for Reinforcement Learning Domains: A Survey.
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- Journal of Machine Learning Research, 2009, v. 10, n. 7, p. 1633
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An Extension on "Statistical Comparisons of Classifiers over Multiple Data Sets" for all Pairwise Comparisons.
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- Journal of Machine Learning Research, 2008, v. 9, n. 12, p. 2677
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JNCC2: The Java Implementation Of Naive Credal Classifier 2.
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- Journal of Machine Learning Research, 2008, v. 9, n. 12, p. 2695
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Double-Bagging Ensemble Using WAVE.
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- Communications for Statistical Applications & Methods, 2014, v. 21, n. 5, p. 411, doi. 10.5351/CSAM.2014.21.5.411
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On effectively predicting autism spectrum disorder therapy using an ensemble of classifiers.
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- Scientific Reports, 2023, v. 13, n. 1, p. 1, doi. 10.1038/s41598-023-46379-3
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Extending XCS with Cyclic Graphs for Scalability on Complex Boolean Problems.
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- Evolutionary Computation, 2017, v. 25, n. 2, p. 173, doi. 10.1162/EVCO_a_00167
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Human-Interpretable Feature Pattern Classification System Using Learning Classifier Systems.
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- Evolutionary Computation, 2014, v. 22, n. 4, p. 629, doi. 10.1162/EVCO_a_00127
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Stochastic vendor selection problem: chance-constrained model and genetic algorithms.
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- Annals of Operations Research, 2009, v. 168, n. 1, p. 169, doi. 10.1007/s10479-008-0367-5
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Die Bismarck - der Arena - das Adler.
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- Zeitschrift für Germanistische Linguistik, 2015, v. 43, n. 2, p. 306, doi. 10.1515/zgl-2015-0016
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Online State Elimination in Accelerated reinforcement Learning.
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- International Journal on Electrical Engineering & Informatics, 2014, v. 6, n. 4, p. 665
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