 | 2009 |
|---|
| 218 |       | Patrick O. Stalph,
Martin V. Butz,
David E. Goldberg,
Xavier Llorà:
On the scalability of XCS(F).
GECCO 2009: 1315-1322 |
| 217 | | Rosane Maria Maffei Vallim,
Thyago S. P. C. Duque,
David E. Goldberg,
André C. P. L. F. Carvalho:
The multi-label OCS with a genetic algorithm for rule discovery: implementation and first results.
GECCO 2009: 1323-1330 |
| 216 | | Thyago S. P. C. Duque,
David E. Goldberg:
A new method for linkage learning in the ECGA.
GECCO 2009: 1819-1820 |
| 215 | | Jose Garcia Moreno-Torres,
Xavier Llorà,
David E. Goldberg:
Binary representation in gene expression programming: towards a better scalability.
GECCO 2009: 1911-1912 |
| 214 | | Elizabeth Radetic,
Martin Pelikan,
David E. Goldberg:
Effects of a deterministic hill climber on hBOA.
GECCO 2009: 437-444 |
| 213 | | Martin Pelikan,
Kumara Sastry,
David E. Goldberg,
Martin V. Butz,
Mark Hauschild:
Performance of evolutionary algorithms on NK landscapes with nearest neighbor interactions and tunable overlap.
GECCO 2009: 851-858 |
| 212 | | Cláudio F. Lima,
Martin Pelikan,
Fernando G. Lobo,
David E. Goldberg:
Loopy Substructural Local Search for the Bayesian Optimization Algorithm.
SLS 2009: 61-75 |
| 2008 |
|---|
| 211 | | Yuji Sato,
David E. Goldberg,
Kumara Sastry:
Improving small population performance under noise with viral infection + tropism.
GECCO 2008: 1143-1144 |
| 210 | | Shunsuke Saruwatari,
Xavier Llorà,
Noriko Imafuji Yasui,
Hiroshi Tamura,
Kumara Sastry,
David E. Goldberg:
Speeding online synthesis via enforced selecto-recombination.
GECCO 2008: 1635-1642 |
| 209 | | Mark Hauschild,
Martin Pelikan,
Kumara Sastry,
David E. Goldberg:
Using previous models to bias structural learning in the hierarchical BOA.
GECCO 2008: 415-422 |
| 208 | | Martin Pelikan,
Kumara Sastry,
David E. Goldberg:
iBOA: the incremental bayesian optimization algorithm.
GECCO 2008: 455-462 |
| 207 | | Thyago S. P. C. Duque,
David E. Goldberg,
Kumara Sastry:
Improving the efficiency of the extended compact genetic algorithm.
GECCO 2008: 467-468 |
| 206 | | Xavier Llorà,
Noriko Imafuji Yasui,
David E. Goldberg:
Graph-theoretic measure for active iGAs: interaction sizing and parallel evaluation ensemble.
GECCO 2008: 985-992 |
| 205 | | Rosane Maria Maffei Vallim,
David E. Goldberg,
Xavier Llorà,
Thyago S. P. C. Duque,
André C. P. L. F. Carvalho:
A new approach for multi-label classification based on default hierarchies and organizational learning.
GECCO (Companion) 2008: 2017-2022 |
| 204 |  | Noriko Imafuji Yasui,
Shunsuke Saruwatari,
Xavier Llorà,
David E. Goldberg:
Facilitation Support for On-Line Focus Group Discussions by Message Feature Map.
ICEIS (2) 2008: 563-566 |
| 203 | | Thyago S. P. C. Duque,
David E. Goldberg,
Kumara Sastry:
Enhancing the Efficiency of the ECGA.
PPSN 2008: 165-174 |
| 202 | | Pier Luca Lanzi,
Luigi Nichetti,
Kumara Sastry,
Davide Voltini,
David E. Goldberg:
Real-Coded Extended Compact Genetic Algorithm Based on Mixtures of Models.
Linkage in Evolutionary Computation 2008: 335-358 |
| 201 | | Minqiang Li,
David E. Goldberg,
Kumara Sastry,
Tian-Li Yu:
Real-Coded ECGA for Solving Decomposable Real-Valued Optimization Problems.
Linkage in Evolutionary Computation 2008: 61-86 |
| 200 | | Cláudio F. Lima,
Martin Pelikan,
David E. Goldberg,
Fernando G. Lobo,
Kumara Sastry,
Mark Hauschild:
Linkage Learning Accuracy in the Bayesian Optimization Algorithm.
Linkage in Evolutionary Computation 2008: 87-107 |
| 199 | | Martin Pelikan,
Kumara Sastry,
David E. Goldberg:
iBOA: The Incremental Bayesian Optimization Algorithm
CoRR abs/0801.3113: (2008) |
| 198 | | Ole J. Mengshoel,
David E. Goldberg:
The Crowding Approach to Niching in Genetic Algorithms.
Evolutionary Computation 16(3): 315-354 (2008) |
| 197 | | Martin Pelikan,
Kumara Sastry,
David E. Goldberg:
Sporadic model building for efficiency enhancement of the hierarchical BOA.
Genetic Programming and Evolvable Machines 9(1): 53-84 (2008) |
| 2007 |
|---|
| 196 | | Kumara Sastry,
David E. Goldberg:
Let's get ready to rumble redux: crossover versus mutation head to head on exponentially scaled problems.
GECCO 2007: 1380-1387 |
| 195 | | Kumara Sastry,
Martin Pelikan,
David E. Goldberg:
Empirical analysis of ideal recombination on random decomposable problems.
GECCO 2007: 1388-1395 |
| 194 | | Xavier Llorà,
Kumara Sastry,
Tian-Li Yu,
David E. Goldberg:
Do not match, inherit: fitness surrogates for genetics-based machine learning techniques.
GECCO 2007: 1798-1805 |
| 193 | | Pier Luca Lanzi,
Martin V. Butz,
David E. Goldberg:
Empirical analysis of generalization and learning in XCS with gradient descent.
GECCO 2007: 1814-1821 |
| 192 | | Albert Orriols-Puig,
David E. Goldberg,
Kumara Sastry,
Ester Bernadó-Mansilla:
Modeling XCS in class imbalances: population size and parameter settings.
GECCO 2007: 1838-1845 |
| 191 | | Albert Orriols-Puig,
Kumara Sastry,
Pier Luca Lanzi,
David E. Goldberg,
Ester Bernadó-Mansilla:
Modeling selection pressure in XCS for proportionate and tournament selection.
GECCO 2007: 1846-1853 |
| 190 | | Kumara Sastry,
David E. Goldberg,
Xavier Llorà:
Towards billion-bit optimization via a parallel estimation of distribution algorithm.
GECCO 2007: 577-584 |
| 189 | | Tian-Li Yu,
Kumara Sastry,
David E. Goldberg,
Martin Pelikan:
Population sizing for entropy-based model building in discrete estimation of distribution algorithms.
GECCO 2007: 601-608 |
| 188 | | Albert Orriols-Puig,
Ester Bernadó-Mansilla,
Kumara Sastry,
David E. Goldberg:
Substructrual surrogates for learning decomposable classification problems: implementation and first results.
GECCO (Companion) 2007: 2875-2882 |
| 187 | | Noriko Imafuji Yasui,
Xavier Llorà,
David E. Goldberg,
Yuichi Washida,
Hiroshi Tamura:
Delineating Topic and Discussant Transitions in Online Collaborative Environments.
ICEIS (2) 2007: 14-21 |
| 186 | | Noriko Imafuji Yasui,
Xavier Llorà,
David E. Goldberg,
Yuichi Washida,
Hiroshi Tamura:
Key Elements Extraction in Online Collaborative Environments.
ICEIS (Selected Papers) 2007: 148-159 |
| 185 | | Cláudio F. Lima,
Martin Pelikan,
David E. Goldberg,
Fernando G. Lobo,
Kumara Sastry,
Mark Hauschild:
Influence of selection and replacement strategies on linkage learning in BOA.
IEEE Congress on Evolutionary Computation 2007: 1083-1090 |
| 184 | | Luca Fossati,
Pier Luca Lanzi,
Kumara Sastry,
David E. Goldberg,
Osvaldo Gómez:
A Simple Real-Coded Extended Compact Genetic Algorithm.
IEEE Congress on Evolutionary Computation 2007: 342-348 |
| 183 | | Xavier Llorà,
Kumara Sastry,
Cláudio F. Lima,
Fernando G. Lobo,
David E. Goldberg:
Linkage Learning, Rule Representation, and the X-Ary Extended Compact Classifier System.
IWLCS 2007: 189-205 |
| 182 | | Albert Orriols-Puig,
Kumara Sastry,
David E. Goldberg,
Ester Bernadó-Mansilla:
Substructural Surrogates for Learning Decomposable Classification Problems.
IWLCS 2007: 235-254 |
| 181 | | Tian-Li Yu,
Kumara Sastry,
David E. Goldberg:
Population Sizing to Go: Online Adaptation Using Noise and Substructural Measurements.
Parameter Setting in Evolutionary Algorithms 2007: 205-223 |
| 180 | | David E. Goldberg,
Kumara Sastry,
Xavier Llorà:
Toward routine billion-variable optimization using genetic algorithms.
Complexity 12(3): 27-29 (2007) |
| 179 | | Pier Luca Lanzi,
Daniele Loiacono,
Stewart W. Wilson,
David E. Goldberg:
Generalization in the XCSF Classifier System: Analysis, Improvement, and Extension.
Evolutionary Computation 15(2): 133-168 (2007) |
| 178 | | Martin V. Butz,
David E. Goldberg,
Pier Luca Lanzi,
Kumara Sastry:
Problem solution sustenance in XCS: Markov chain analysis of niche support distributions and the impact on computational complexity.
Genetic Programming and Evolvable Machines 8(1): 5-37 (2007) |
| 177 | | Naohiro Matsumura,
David E. Goldberg,
Xavier Llorà:
Communication Gap Management for Fertile Community.
Soft Comput. 11(8): 791-798 (2007) |
| 2006 |
|---|
| 176 | | Kumara Sastry,
Paul Winward,
David E. Goldberg,
Cláudio F. Lima:
Fluctuating Crosstalk as a Source of Deterministic Noise and Its Effects on GA Scalability.
EvoWorkshops 2006: 740-751 |
| 175 | | Paul Winward,
David E. Goldberg:
Fluctuating crosstalk, deterministic noise, and GA scalability.
GECCO 2006: 1361-1368 |
| 174 | | Tian-Li Yu,
David E. Goldberg:
Conquering hierarchical difficulty by explicit chunking: substructural chromosome compression.
GECCO 2006: 1385-1392 |
| 173 | | Xavier Llorà,
Kumara Sastry,
Francesc Alías,
David E. Goldberg,
Michael Welge:
Analyzing active interactive genetic algorithms using visual analytics.
GECCO 2006: 1417-1418 |
| 172 | | Pier Luca Lanzi,
Daniele Loiacono,
Stewart W. Wilson,
David E. Goldberg:
Classifier prediction based on tile coding.
GECCO 2006: 1497-1504 |
| 171 | | Pier Luca Lanzi,
Daniele Loiacono,
Stewart W. Wilson,
David E. Goldberg:
Prediction update algorithms for XCSF: RLS, Kalman filter, and gain adaptation.
GECCO 2006: 1505-1512 |
| 170 | | Kumara Sastry,
D. D. Johnson,
Alexis L. Thompson,
David E. Goldberg,
Todd J. Martinez,
Jeff Leiding,
Jane Owens:
Multiobjective genetic algorithms for multiscaling excited state direct dynamics in photochemistry.
GECCO 2006: 1745-1752 |
| 169 | | Martin Pelikan,
Kumara Sastry,
David E. Goldberg:
Sporadic model building for efficiency enhancement of hierarchical BOA.
GECCO 2006: 405-412 |
| 168 | | Kumara Sastry,
Cláudio F. Lima,
David E. Goldberg:
Evaluation relaxation using substructural information and linear estimation.
GECCO 2006: 419-426 |
| 167 | | Martin Pelikan,
Kumara Sastry,
Martin V. Butz,
David E. Goldberg:
Hierarchical BOA on random decomposable problems.
GECCO 2006: 431-432 |
| 166 | | Cláudio F. Lima,
Martin Pelikan,
Kumara Sastry,
Martin V. Butz,
David E. Goldberg,
Fernando G. Lobo:
Substructural Neighborhoods for Local Search in the Bayesian Optimization Algorithm.
PPSN 2006: 232-241 |
| 165 | | Martin Pelikan,
Kumara Sastry,
Martin V. Butz,
David E. Goldberg:
Performance of Evolutionary Algorithms on Random Decomposable Problems.
PPSN 2006: 788-797 |
| 164 | | Kumara Sastry,
Martin Pelikan,
David E. Goldberg:
Efficiency Enhancement of Estimation of Distribution Algorithms.
Scalable Optimization via Probabilistic Modeling 2006: 161-185 |
| 163 | | Martin Pelikan,
Kumara Sastry,
David E. Goldberg:
Multiobjective Estimation of Distribution Algorithms.
Scalable Optimization via Probabilistic Modeling 2006: 223-248 |
| 162 | | Martin Butz,
Martin Pelikan,
Xavier Llorà,
David E. Goldberg:
Effective and Reliable Online Classification Combining XCS with EDA Mechanisms.
Scalable Optimization via Probabilistic Modeling 2006: 249-273 |
| 161 | | Tian-Li Yu,
Scott Santarelli,
David E. Goldberg:
Military Antenna Design Using a Simple Genetic Algorithm and hBOA.
Scalable Optimization via Probabilistic Modeling 2006: 275-289 |
| 160 | | Martin Pelikan,
David E. Goldberg:
Hierarchical Bayesian Optimization Algorithm.
Scalable Optimization via Probabilistic Modeling 2006: 63-90 |
| 159 | | Martin V. Butz,
Martin Pelikan,
Xavier Llorà,
David E. Goldberg:
Automated Global Structure Extraction for Effective Local Building Block Processing in XCS.
Evolutionary Computation 14(3): 345-380 (2006) |
| 2005 |
|---|
| 158 | | David E. Goldberg:
Little Models, Big Results.
Australian Conference on Artificial Intelligence 2005: 4 |
| 157 | | Pier Luca Lanzi,
Daniele Loiacono,
Stewart W. Wilson,
David E. Goldberg:
XCS with computed prediction in continuous multistep environments.
Congress on Evolutionary Computation 2005: 2032-2039 |
| 156 | | Kumara Sastry,
David E. Goldberg,
Martin Pelikan:
Limits of scalability of multiobjective estimation of distribution algorithms.
Congress on Evolutionary Computation 2005: 2217-2224 |
| 155 | | Tian-Li Yu,
Kumara Sastry,
David E. Goldberg:
Online population size adjusting using noise and substructural measurements.
Congress on Evolutionary Computation 2005: 2491-2498 |
| 154 | | Pier Luca Lanzi,
Daniele Loiacono,
Stewart W. Wilson,
David E. Goldberg:
XCS with computed prediction for the learning of Boolean functions.
Congress on Evolutionary Computation 2005: 588-595 |
| 153 | | Xavier Llorà,
Kumara Sastry,
David E. Goldberg:
The compact classifier system: scalability analysis and first results.
Congress on Evolutionary Computation 2005: 596-603 |
| 152 | | Tian-Li Yu,
Kumara Sastry,
David E. Goldberg:
Linkage learning, overlapping building blocks, and systematic strategy for scalable recombination.
GECCO 2005: 1217-1224 |
| 151 | | Xavier Llorà,
Kumara Sastry,
David E. Goldberg,
Abhimanyu Gupta,
Lalitha Lakshmi:
Combating user fatigue in iGAs: partial ordering, support vector machines, and synthetic fitness.
GECCO 2005: 1363-1370 |
| 150 | | Jian-Hung Chen,
Shinn-Ying Ho,
David E. Goldberg:
Quality-time analysis of multi-objective evolutionary algorithms.
GECCO 2005: 1455-1462 |
| 149 | | Pier Luca Lanzi,
Daniele Loiacono,
Stewart W. Wilson,
David E. Goldberg:
Extending XCSF beyond linear approximation.
GECCO 2005: 1827-1834 |
| 148 | | Pier Luca Lanzi,
Daniele Loiacono,
Stewart W. Wilson,
David E. Goldberg:
XCS with computed prediction in multistep environments.
GECCO 2005: 1859-1866 |
| 147 | | Xavier Llorà,
Kumara Sastry,
David E. Goldberg:
The compact classifier system: motivation, analysis, and first results.
GECCO 2005: 1993-1994 |
| 146 | | Martin V. Butz,
Martin Pelikan,
Xavier Llorà,
David E. Goldberg:
Extracted global structure makes local building block processing effective in XCS.
GECCO 2005: 655-662 |
| 145 | | Martin Pelikan,
Kumara Sastry,
David E. Goldberg:
Multiobjective hBOA, clustering, and scalability.
GECCO 2005: 663-670 |
| 144 | | Kumara Sastry,
Hussein A. Abbass,
David E. Goldberg,
D. D. Johnson:
Sub-structural niching in estimation of distribution algorithms.
GECCO 2005: 671-678 |
| 143 | | Cláudio F. Lima,
Kumara Sastry,
David E. Goldberg,
Fernando G. Lobo:
Combining competent crossover and mutation operators: a probabilistic model building approach.
GECCO 2005: 735-742 |
| 142 | | Xavier Llorà,
Kumara Sastry,
David E. Goldberg:
Binary rule encoding schemes: a study using the compact classifier system.
GECCO Workshops 2005: 88-89 |
| 141 | | Arnaud Quirin,
Jerzy J. Korczak,
Martin V. Butz,
David E. Goldberg:
Analysis and Evaluation of Learning Classifier Systems applied to Hyperspectral Image Classification.
ISDA 2005: 280-285 |
| 140 | | Martin V. Butz,
David E. Goldberg,
Pier Luca Lanzi:
Effect of Pure Error-Based Fitness in XCS.
IWLCS 2005: 104-114 |
| 139 | | Jaume Bacardit,
David E. Goldberg,
Martin V. Butz:
Improving the Performance of a Pittsburgh Learning Classifier System Using a Default Rule.
IWLCS 2005: 291-307 |
| 138 | | Xavier Llorà,
Kumara Sastry,
David E. Goldberg:
Binary Rule Encoding Schemes: A Study Using the Compact Classifier System.
IWLCS 2005: 40-58 |
| 137 | | Naohiro Matsumura,
David E. Goldberg,
Xavier Llorà:
Communication Gaps in Social Networks.
WSTST 2005: 543-552 |
| 136 | | Naohiro Matsumura,
David E. Goldberg,
Xavier Llorà:
Mining directed social network from message board.
WWW (Special interest tracks and posters) 2005: 1092-1093 |
| 135 | | Kumara Sastry,
Una-May O'Reilly,
David E. Goldberg:
Population Sizing for Genetic Programming Based Upon Decision Making
CoRR abs/cs/0502020: (2005) |
| 134 | | Hussein A. Abbass,
Kumara Sastry,
David E. Goldberg:
Oiling the Wheels of Change: The Role of Adaptive Automatic Problem Decomposition in Non-Stationary Environments
CoRR abs/cs/0502021: (2005) |
| 133 | | Kumara Sastry,
Hussein A. Abbass,
David E. Goldberg:
Sub-Structural Niching in Non-Stationary Environments
CoRR abs/cs/0502022: (2005) |
| 132 | | Kumara Sastry,
Hussein A. Abbass,
David E. Goldberg,
D. D. Johnson:
Sub-structural Niching in Estimation of Distribution Algorithms
CoRR abs/cs/0502023: (2005) |
| 131 | | Martin Pelikan,
Kumara Sastry,
David E. Goldberg:
Multiobjective hBOA, Clustering, and Scalability
CoRR abs/cs/0502034: (2005) |
| 130 | | Kumara Sastry,
Martin Pelikan,
David E. Goldberg:
Decomposable Problems, Niching, and Scalability of Multiobjective Estimation of Distribution Algorithms
CoRR abs/cs/0502057: (2005) |
| 129 | | Ying-Ping Chen,
David E. Goldberg:
Convergence Time for the Linkage Learning Genetic Algorithm.
Evolutionary Computation 13(3): 279-302 (2005) |
| 128 | | Laura A. McLay,
David E. Goldberg:
Efficient Genetic Algorithms Using Discretization Scheduling.
Evolutionary Computation 13(3): 353-385 (2005) |
| 127 | | Martin V. Butz,
Kumara Sastry,
David E. Goldberg:
Strong, Stable, and Reliable Fitness Pressure in XCS due to Tournament Selection.
Genetic Programming and Evolvable Machines 6(1): 53-77 (2005) |
| 126 | | Martin V. Butz,
David E. Goldberg,
Pier Luca Lanzi:
Gradient descent methods in learning classifier systems: improving XCS performance in multistep problems.
IEEE Trans. Evolutionary Computation 9(5): 452-473 (2005) |
| 2004 |
|---|
| 125 | | Kumara Sastry,
Hussein A. Abbass,
David E. Goldberg:
Sub-structural Niching in Non-stationary Environments.
Australian Conference on Artificial Intelligence 2004: 873-885 |
| 124 | | Kei Ohnishi,
Kumara Sastry,
Ying-Ping Chen,
David E. Goldberg:
Inducing Sequentiality Using Grammatical Genetic Codes.
GECCO (1) 2004: 1426-1437 |
| 123 | | Chang Wook Ahn,
Rudrapatna S. Ramakrishna,
David E. Goldberg:
Real-Coded Bayesian Optimization Algorithm: Bringing the Strength of BOA into the Continuous World.
GECCO (1) 2004: 840-851 |
| 122 | | Ying-Ping Chen,
David E. Goldberg:
Introducing Subchromosome Representations to the Linkage Learning Genetic Algorithm.
GECCO (1) 2004: 971-982 |
| 121 | | Gerulf K. M. Pedersen,
David E. Goldberg:
Dynamic Uniform Scaling for Multiobjective Genetic Algorithms.
GECCO (2) 2004: 11-23 |
| 120 | | Kumara Sastry,
David E. Goldberg:
Designing Competent Mutation Operators Via Probabilistic Model Building of Neighborhoods.
GECCO (2) 2004: 114-125 |
| 119 | | Kumara Sastry,
David E. Goldberg:
Let's Get Ready to Rumble: Crossover Versus Mutation Head to Head.
GECCO (2) 2004: 126-137 |
| 118 | | Xavier Llorà,
Kei Ohnishi,
Ying-Ping Chen,
David E. Goldberg,
Michael Welge:
Enhanced Innovation: A Fusion of Chance Discovery and Evolutionary Computation to Foster Creative Processes and Decision Making.
GECCO (2) 2004: 1314-1315 |
| 117 | | Tian-Li Yu,
David E. Goldberg:
Dependency Structure Matrix Analysis: Offline Utility of the Dependency Structure Matrix Genetic Algorithm.
GECCO (2) 2004: 355-366 |
| 116 | | Tian-Li Yu,
David E. Goldberg:
Toward an Understanding of the Quality and Efficiency of Model Building for Genetic Algorithms.
GECCO (2) 2004: 367-378 |
| 115 | | Martin V. Butz,
David E. Goldberg,
Pier Luca Lanzi:
Bounding Learning Time in XCS.
GECCO (2) 2004: 739-750 |
| 114 | | Martin V. Butz,
David E. Goldberg,
Pier Luca Lanzi:
Gradient-Based Learning Updates Improve XCS Performance in Multistep Problems.
GECCO (2) 2004: 751-762 |
| 113 | | Jaume Bacardit,
David E. Goldberg,
Martin V. Butz,
Xavier Llorà,
Josep Maria Garrell i Guiu:
Speeding-Up Pittsburgh Learning Classifier Systems: Modeling Time and Accuracy.
PPSN 2004: 1021-1031 |
| 112 | | Martin V. Butz,
Pier Luca Lanzi,
Xavier Llorà,
David E. Goldberg:
Knowledge Extraction and Problem Structure Identification in XCS.
PPSN 2004: 1051-1060 |
| 111 | | Kumara Sastry,
David E. Goldberg,
Martin Pelikan:
Efficiency Enhancement of Probabilistic Model Building Genetic Algorithms
CoRR cs.NE/0405062: (2004) |
| 110 | | Kumara Sastry,
David E. Goldberg:
Let's Get Ready to Rumble: Crossover Versus Mutation Head to Head
CoRR cs.NE/0405063: (2004) |
| 109 | | Kumara Sastry,
David E. Goldberg:
Designing Competent Mutation Operators via Probabilistic Model Building of Neighborhoods
CoRR cs.NE/0405064: (2004) |
| 108 | | Kumara Sastry,
Martin Pelikan,
David E. Goldberg:
Efficiency Enhancement of Genetic Algorithms via Building-Block-Wise Fitness Estimation
CoRR cs.NE/0405065: (2004) |
| 107 | | Fernando G. Lobo,
David E. Goldberg:
The parameter-less genetic algorithm in practice.
Inf. Sci. 167(1-4): 217-232 (2004) |
| 2003 |
|---|
| 106 | | Martin Butz,
David E. Goldberg:
Generalized State Values in an Anticipatory Learning Classifier System.
Anticipatory Behavior in Adaptive Learning Systems 2003: 282-301 |
| 105 | | Xavier Llorà,
David E. Goldberg:
Wise Breeding GA via Machine Learning Techniques for Function Optimization.
GECCO 2003: 1172-1183 |
| 104 | | Martin Pelikan,
David E. Goldberg:
Hierarchical BOA Solves Ising Spin Glasses and MAXSAT.
GECCO 2003: 1271-1282 |
| 103 | | Kumara Sastry,
David E. Goldberg:
Scalability of Selectorecombinative Genetic Algorithms for Problems with Tight Linkage.
GECCO 2003: 1332-1344 |
| 102 | | Tian-Li Yu,
David E. Goldberg,
Kumara Sastry:
Optimal Sampling and Speed-Up for Genetic Algorithms on the Sampled OneMax Problem.
GECCO 2003: 1554-1565 |
| 101 | | Tian-Li Yu,
David E. Goldberg,
Ali Yassine,
Ying-Ping Chen:
Genetic Algorithm Design Inspired by Organizational Theory: Pilot Study of a Dependency Structure Matrix Driven Genetic Algorithm.
GECCO 2003: 1620-1621 |
| 100 | | Martin Butz,
David E. Goldberg:
Bounding the Population Size in XCS to Ensure Reproductive Opportunities.
GECCO 2003: 1844-1856 |
| 99 | | Martin Butz,
Kumara Sastry,
David E. Goldberg:
Tournament Selection: Stable Fitness Pressure in XCS.
GECCO 2003: 1857-1869 |
| 98 | | Kurian K. Tharakunnel,
Martin Butz,
David E. Goldberg:
Towards Building Block Propagation in XCS: A Negative Result and Its Implications.
GECCO 2003: 1906-1917 |
| 97 | | Erick Cantú-Paz,
David E. Goldberg:
Are Multiple Runs of Genetic Algorithms Better than One?
GECCO 2003: 801-812 |
| 96 | | Ying-Ping Chen,
David E. Goldberg:
An Analysis of a Reordering Operator with Tournament Selection on a GA-Hard Problem.
GECCO 2003: 825-836 |
| 95 | | Ying-Ping Chen,
David E. Goldberg:
Tightness Time for the Linkage Learning Genetic Algorithm.
GECCO 2003: 837-849 |
| 94 | | Felipe P. Espinoza,
Barbara S. Minsker,
David E. Goldberg:
Performance Evaluation and Population Reduction for a Self Adaptive Hybrid Genetic Algorithm (SAHGA).
GECCO 2003: 922-933 |
| 93 | | Chang Wook Ahn,
David E. Goldberg,
Rudrapatna S. Ramakrishna:
Multiple-Deme Parallel Estimation of Distribution Algorithms: Basic Framework and Application.
PPAM 2003: 544-551 |
| 92 | | David E. Goldberg,
Kumara Sastry,
Yukio Ohsawa:
Discovering Deep Building Blocks for Competent Genetic Algorithms Using Chance Discovery via KeyGraphs.
Chance Discovery 2003: 276-302 |
| 91 | | Martin Pelikan,
David E. Goldberg:
A hierarchy machine: Learning to optimize from nature and humans.
Complexity 8(5): 36-45 (2003) |
| 90 | | Martin Butz,
David E. Goldberg,
Kurian K. Tharakunnel:
Analysis and Improvement of Fitness Exploitation in XCS: Bounding Models, Tournament Selection, and Bilateral Accuracy.
Evolutionary Computation 11(3): 239-277 (2003) |
| 89 | | Xavier Llorà,
David E. Goldberg:
Bounding the effect of noise in Multiobjective Learning Classifier Systems.
Evolutionary Computation 11(3): 278-297 (2003) |
| 88 | | Franz Rothlauf,
David E. Goldberg:
Redundant Representations in Evolutionary Computation.
Evolutionary Computation 11(4): 381-415 (2003) |
| 87 | | Martin Pelikan,
David E. Goldberg,
Shigeyoshi Tsutsui:
Getting the best of both worlds: Discrete and continuous genetic and evolutionary algorithms in concert.
Inf. Sci. 156(3-4): 147-171 (2003) |
| 2002 |
|---|
| 86 | | Laura A. Albert,
David E. Goldberg:
Efficient Discretization Scheduling In Multiple Dimensions.
GECCO 2002: 271-278 |
| 85 | | Jian-Hung Chen,
David E. Goldberg,
Shinn-Ying Ho,
Kumara Sastry:
Fitness Inheritance In Multi-objective Optimization.
GECCO 2002: 319-326 |
| 84 | | Martin Pelikan,
David E. Goldberg,
Shigeyoshi Tsutsui:
Combining The Strengths Of Bayesian Optimization Algorithm And Adaptive Evolution Strategies.
GECCO 2002: 512-519 |
| 83 | | Kumara Sastry,
David E. Goldberg:
Genetic Algorithms, Efficiency Enhancement, And Deciding Well With Differing Fitness Variances.
GECCO 2002: 528-535 |
| 82 | | Kumara Sastry,
David E. Goldberg:
Genetic Algorithms, Efficiency Enhancement, And Deciding Well With Differing Fitness Bias Values.
GECCO 2002: 536-543 |
| 81 | | Clarissa Van Hoyweghen,
David E. Goldberg,
Bart Naudts:
From Twomax To The Ising Model: Easy And Hard Symmetrical Problems.
GECCO 2002: 626-633 |
| 80 | | Nazan Khan,
David E. Goldberg,
Martin Pelikan:
Multiple-objective Bayesian Optimization Algorithm.
GECCO 2002: 684 |
| 79 | | Abhishek Singh,
David E. Goldberg,
Ying-Ping Chen:
Modified Linkage Learning Genetic Algorithm For Difficult Non-stationary Problems.
GECCO 2002: 699 |
| 78 | | Alexander Kosorukoff,
David E. Goldberg:
Evolutionary Computation As A Form Of Organization.
GECCO 2002: 965-972 |
| 77 | | Abhishek Singh,
David E. Goldberg,
Ying-Ping Chen:
Modified Linkage Learning Genetic Algorithm for Difficult Non-Stationary Problems.
GECCO Late Breaking Papers 2002: 419-426 |
| 76 | | Xavier Llorà,
David E. Goldberg,
Ivan Traus,
Ester Bernadó i Mansilla:
Accuracy, Parsimony, and Generality in Evolutionary Learning Systems via Multiobjective Selection.
IWLCS 2002: 118-142 |
| 75 | | Ying-Ping Chen,
David E. Goldberg:
Introducing Start Expression Genes to the Linkage Learning Genetic Algorithm.
PPSN 2002: 351-360 |
| 74 | | Franz Rothlauf,
David E. Goldberg,
Armin Heinzl:
Network Random Keys-A Tree Representation Scheme for Genetic and Evolutionary Algorithms.
Evolutionary Computation 10(1): 75-97 (2002) |
| 73 | | Clarissa Van Hoyweghen,
Bart Naudts,
David E. Goldberg:
Spin-Flip Symmetry and Synchronization.
Evolutionary Computation 10(4): 317-344 (2002) |
| 72 | | Martin Pelikan,
Kumara Sastry,
David E. Goldberg:
Scalability of the Bayesian optimization algorithm.
Int. J. Approx. Reasoning 31(3): 221-258 (2002) |
| 2001 |
|---|
| 71 | | Shigeyoshi Tsutsui,
David E. Goldberg:
Search space boundary extension method in real-coded genetic algorithms.
Inf. Sci. 133(3-4): 229-247 (2001) |
| 2000 |
|---|
| 70 | | L. Darrell Whitley,
David E. Goldberg,
Erick Cantú-Paz,
Lee Spector,
Ian C. Parmee,
Hans-Georg Beyer:
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '00), Las Vegas, Nevada, USA, July 8-12, 2000
Morgan Kaufmann 2000 |
| 69 | | Fernando G. Lobo,
David E. Goldberg,
Martin Pelikan:
Time Complexity of genetic algorithms on exponentially scaled problems.
GECCO 2000: 151-158 |
| 68 | | Dimitri Knjazew,
David E. Goldberg:
OMEGA - Ordering Messy GA: Solving Permutation Problems with the Fast Genetic Algorithm and Random Keys.
GECCO 2000: 181-188 |
| 67 | | Martin Pelikan,
David E. Goldberg:
Hierarchical Problem Solving and the Bayesian Optimization Algorithm.
GECCO 2000: 267-274 |
| 66 | | Martin Pelikan,
David E. Goldberg,
Erick Cantú-Paz:
Bayesian Optimization Algorithm, Population Sizing, and Time to Convergence.
GECCO 2000: 275-282 |
| 65 | | Franz Rothlauf,
David E. Goldberg,
Armin Heinzl:
Bad Codings and the Utility of Well-Designed Genetic Algorithms.
GECCO 2000: 355-364 |
| 64 | | Martin Butz,
David E. Goldberg,
Wolfgang Stolzmann:
Introducing a Genetic Generalization Pressure to the Anticipatory Classifier System - Part 1: Theoretical approach.
GECCO 2000: 42-49 |
| 63 | | Martin Butz,
David E. Goldberg,
Wolfgang Stolzmann:
Probability-Enhanced Predictions in the Anticipatory Classifier System.
IWLCS 2000: 37-51 |
| 62 | | Martin Pelikan,
David E. Goldberg:
Genetic Algorithms, Clustering, and the Breaking of Symmetry.
PPSN 2000: 385-394 |
| 61 | | Franz Rothlauf,
David E. Goldberg:
Pruefer Numbers and Genetic Algorithms: A Lesson on How the Low Locality of an Encoding Can Harm the Performance of GAs.
PPSN 2000: 395-404 |
| 60 | | Dimitri Knjazew,
David E. Goldberg:
Large-Scale Permutation Optimization with the Ordering Messy Genetic Algorithm.
PPSN 2000: 631-640 |
| 59 | | Martin Butz,
David E. Goldberg,
Wolfgang Stolzmann:
Investigating Generalization in the Anticipatory Classifier System.
PPSN 2000: 735-744 |
| 58 | | Martin Pelikan,
David E. Goldberg,
Erick Cantú-Paz:
Linkage Problem, Distribution Estimation, and Bayesian Networks.
Evolutionary Computation 8(3): 311-340 (2000) |
| 1999 |
|---|
| 57 | | David E. Goldberg:
Using Time Efficiently: Genetic-Evolutionary Algorithms and the Continuation Problem.
GECCO 1999: 212-219 |
| 56 | | David E. Goldberg,
Siegfried Vössner:
Optimizing Global-Local Search Hybrids.
GECCO 1999: 220-228 |
| 55 | | John H. Holland,
Lashon B. Booker,
Marco Colombetti,
Marco Dorigo,
David E. Goldberg,
Stephanie Forrest,
Rick L. Riolo,
Robert E. Smith,
Pier Luca Lanzi,
Wolfgang Stolzmann,
Stewart W. Wilson:
What Is a Learning Classifier System?
Learning Classifier Systems 1999: 3-32 |
| 54 | | J. L. Schlabach,
C. C. Hayes,
David E. Goldberg:
FOX-GA: A Genetic Algorithm for Generating and Analyzing Battlefield Courses of Action.
Evolutionary Computation 7(1): 45-68 (1999) |
| 53 | | Georges R. Harik,
Erick Cantú-Paz,
David E. Goldberg,
Brad L. Miller:
The Gambler's Ruin Problem, Genetic Algorithms, and the Sizing of Populations.
Evolutionary Computation 7(3): 231-253 (1999) |
| 52 | | Masaharu Munetomo,
David E. Goldberg:
Linkage Identification by Non-monotonicity Detection for Overlapping Functions.
Evolutionary Computation 7(4): 377-398 (1999) |
| 51 | | Erick Cantú-Paz,
David E. Goldberg:
On the Scalability of Parallel Genetic Algorithms.
Evolutionary Computation 7(4): 429-449 (1999) |
| 50 | | John R. Koza,
Wolfgang Banzhaf,
Kumar Chellapilla,
Kalyanmoy Deb,
Marco Dorigo,
David B. Fogel,
Max H. Garzon,
David E. Goldberg,
Hitoshi Iba,
Rick L. Riolo:
Genetic Programming 1998: Proceedings of the Third Annual Conference.
IEEE Trans. Evolutionary Computation 3(2): 159-161 (1999) |
| 49 | | Georges R. Harik,
Fernando G. Lobo,
David E. Goldberg:
The compact genetic algorithm.
IEEE Trans. Evolutionary Computation 3(4): 287-297 (1999) |
| 1998 |
|---|
| 48 | | David E. Goldberg,
Una-May O'Reilly:
Where Does the Good Stuff Go, and Why? How Contextual Semantics Influences Program Structure in Simple Genetic Programming.
EuroGP 1998: 16-36 |
| 47 | | Jeffrey Horn,
David E. Goldberg:
Toward a Control Map for Niching.
FOGA 1998: 287-310 |
| 46 | | Jeffrey Horn,
David E. Goldberg:
A Timing Analysis of Convergence to Fitness Sharing Equilibrium.
PPSN 1998: 23-33 |
| 1997 |
|---|
| 45 | | Erick Cantú-Paz,
David E. Goldberg:
Predicting Speedups of Ideal Bounding Cases of Parallel Genetic Algorithms.
ICGA 1997: 113-120 |
| 44 | | Yuji Sakamoto,
David E. Goldberg:
Takeover Time in a Noisy Environment.
ICGA 1997: 160-165 |
| 1996 |
|---|
| 43 | | Georges R. Harik,
David E. Goldberg:
Learning Linkage.
FOGA 1996: 247-262 |
| 42 | | Hillol Kargupta,
David E. Goldberg:
SEARCH, Blackbox Optimization, And Sample Complexity.
FOGA 1996: 291-324 |
| 41 | | Hillol Kargupta,
David E. Goldberg:
Polynominal Complexity Blackbox Search: Lessons From the SEARCH Framework.
International Conference on Evolutionary Computation 1996: 792-797 |
| 40 | | Brad L. Miller,
David E. Goldberg:
Genetic Algorithms, Selection Schemes, and the Varying Effects of Noise.
Evolutionary Computation 4(2): 113-131 (1996) |
| 1995 |
|---|
| 39 | | Samir W. Mahfoud,
David E. Goldberg:
Parallel Recombinative Simulated Annealing: A Genetic Algorithm.
Parallel Computing 21(1): 1-28 (1995) |
| 1994 |
|---|
| 38 | | Jeffrey Horn,
David E. Goldberg:
Genetic Algorithm Difficulty and the Modality of Fitness Landscapes.
FOGA 1994: 243-269 |
| 37 | | Dirk Thierens,
David E. Goldberg:
Elitist Recombination: An Integrated Selection Recombination GA.
International Conference on Evolutionary Computation 1994: 508-512 |
| 36 | | Jeffrey Horn,
Nicholas Nafpliotis,
David E. Goldberg:
A Niched Pareto Genetic Algorithm for Multiobjective Optimization.
International Conference on Evolutionary Computation 1994: 82-87 |
| 35 | | Dirk Thierens,
David E. Goldberg:
Convergence Models of Genetic Algorithm Selection Schemes.
PPSN 1994: 119-129 |
| 34 | | Jeffrey Horn,
David E. Goldberg,
Kalyanmoy Deb:
Long Path Problems.
PPSN 1994: 149-158 |
| 33 | | David E. Goldberg:
Genetic and Evolutionary Algorithms Come of Age.
Commun. ACM 37(3): 113-119 (1994) |
| 32 | | Jeffrey Horn,
David E. Goldberg,
Kalyanmoy Deb:
Implicit Niching in a Learning Classifier System: Nature's Way.
Evolutionary Computation 2(1): 37-66 (1994) |
| 1993 |
|---|
| 31 | | Dirk Thierens,
David E. Goldberg:
Mixing in Genetic Algorithms.
ICGA 1993: 38-47 |
| 30 | | David E. Goldberg,
Kalyanmoy Deb,
Hillol Kargupta,
Georges R. Harik:
RapidAccurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms.
ICGA 1993: 56-64 |
| 29 | | Kalyanmoy Deb,
David E. Goldberg:
Sufficient Conditions for Deceptive and Easy Binary Functions.
Ann. Math. Artif. Intell. 10(4): 385-408 (1993) |
| 1992 |
|---|
| 28 | | David E. Goldberg,
Kalyanmoy Deb,
James H. Clark:
Accounting for Noise in the Sizing of Populations.
FOGA 1992: 127-140 |
| 27 | | Kalyanmoy Deb,
David E. Goldberg:
Analyzing Deception in Trap Functions.
FOGA 1992: 93-108 |
| 26 | | Samir W. Mahfoud,
David E. Goldberg:
A Genetic Algorithm for Parallel Simulated Annealing.
PPSN 1992: 303-312 |
| 25 | | David E. Goldberg,
Kalyanmoy Deb,
Jeffrey Horn:
Massive Multimodality, Deception, and Genetic Algorithms.
PPSN 1992: 37-48 |
| 24 | | Hillol Kargupta,
Kalyanmoy Deb,
David E. Goldberg:
Ordering Genetic Algorithms and Deception.
PPSN 1992: 49-58 |
| 23 | | David E. Goldberg:
Construction of High-Order Deceptive Functions Using Low-Order Walsh Coefficients.
Ann. Math. Artif. Intell. 5(1): 35-47 (1992) |
| 22 | | Robert E. Smith,
David E. Goldberg:
Reinforcement learning with classifier systems: Adaptive default hierarchy formation.
Applied Artificial Intelligence 6(1): 79-102 (1992) |
| 1991 |
|---|
| 21 | | David E. Goldberg,
Kalyanmoy Deb,
Bradley Korb:
Don't Worry, Be Messy.
ICGA 1991: 24-30 |
| 20 | | Andrew Horner,
David E. Goldberg:
Genetic Algorithms and Computer-Assisted Music Composition.
ICGA 1991: 437-441 |
| 1990 |
|---|
| 19 | | Clayton L. Bridges,
David E. Goldberg:
The Nonuniform Walsh-Schema Transform.
FOGA 1990: 13-22 |
| 18 | | Robert E. Smith,
David E. Goldberg:
Variable Default Hierarchy Separation in a Classifier System.
FOGA 1990: 148-167 |
| 17 | | David E. Goldberg,
Kalyanmoy Deb:
A Comparative Analysis of Selection Schemes Used in Genetic Algorithms.
FOGA 1990: 69-93 |
| 16 | | David E. Goldberg:
The Theory of Virtual Alphabets.
PPSN 1990: 13-22 |
| 15 | | David E. Goldberg:
Probability Matching, the Magnitude of Reinforcement, and Classifier System Bidding.
Machine Learning 5: 407-425 (1990) |
| 1989 |
|---|
| 14 | | David E. Goldberg:
Genetic Algorithms in Search Optimization and Machine Learning
Addison-Wesley 1989 |
| 13 | | Stewart W. Wilson,
David E. Goldberg:
A Critical Review of Classifier Systems.
ICGA 1989: 244-255 |
| 12 | | Kalyanmoy Deb,
David E. Goldberg:
An Investigation of Niche and Species Formation in Genetic Function Optimization.
ICGA 1989: 42-50 |
| 11 | | David E. Goldberg:
Sizing Populations for Serial and Parallel Genetic Algorithms.
ICGA 1989: 70-79 |
| 10 | | David E. Goldberg:
Zen and the Art of Genetic Algorithms.
ICGA 1989: 80-85 |
| 9 | | Lashon B. Booker,
David E. Goldberg,
John H. Holland:
Classifier Systems and Genetic Algorithms.
Artif. Intell. 40(1-3): 235-282 (1989) |
| 1988 |
|---|
| 8 | | David E. Goldberg,
John H. Holland:
Genetic Algorithms and Machine Learning.
Machine Learning 3: 95-99 (1988) |
| 1987 |
|---|
| 7 | | David E. Goldberg,
Philip Segrest:
Finite Markov Chain Analysis of Genetic Algorithms.
ICGA 1987: 1-8 |
| 6 | | David E. Goldberg,
Jon Richardson:
Genetic Algorithms with Sharing for Multimodalfunction Optimization.
ICGA 1987: 41-49 |
| 5 | | David E. Goldberg,
Robert E. Smith:
Nonstationary Function Optimization Using Genetic Algorithms with Dominance and Diploidy.
ICGA 1987: 59-68 |
| 4 | | Clayton L. Bridges,
David E. Goldberg:
An Analysis of Reproduction and Crossover in a Binary-Coded Genetic Algorithm.
ICGA 1987: 9-13 |
| 1985 |
|---|
| 3 | | David E. Goldberg,
Robert Lingle Jr.:
AllelesLociand the Traveling Salesman Problem.
ICGA 1985: 154-159 |
| 2 | | David E. Goldberg:
Genetic Algorithms and Rules Learning in Dynamic System Control.
ICGA 1985: 8-15 |
| 1 | | David E. Goldberg:
Dynamic System Control Using Rule Learning and Genetic Algorithms.
IJCAI 1985: 588-592 |
