2008 | ||
---|---|---|
211 | EE | Yuji Sato, David E. Goldberg, Kumara Sastry: Improving small population performance under noise with viral infection + tropism. GECCO 2008: 1143-1144 |
210 | EE | 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 | EE | 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 | EE | Martin Pelikan, Kumara Sastry, David E. Goldberg: iBOA: the incremental bayesian optimization algorithm. GECCO 2008: 455-462 |
207 | EE | Thyago S. P. C. Duque, David E. Goldberg, Kumara Sastry: Improving the efficiency of the extended compact genetic algorithm. GECCO 2008: 467-468 |
206 | EE | 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 | EE | Rosane M. M. 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 | EE | Thyago S. P. C. Duque, David E. Goldberg, Kumara Sastry: Enhancing the Efficiency of the ECGA. PPSN 2008: 165-174 |
202 | EE | 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 | EE | 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 | EE | 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 | EE | Martin Pelikan, Kumara Sastry, David E. Goldberg: iBOA: The Incremental Bayesian Optimization Algorithm CoRR abs/0801.3113: (2008) |
198 | EE | Ole J. Mengshoel, David E. Goldberg: The Crowding Approach to Niching in Genetic Algorithms. Evolutionary Computation 16(3): 315-354 (2008) |
197 | EE | 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 | EE | 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 | EE | Kumara Sastry, Martin Pelikan, David E. Goldberg: Empirical analysis of ideal recombination on random decomposable problems. GECCO 2007: 1388-1395 |
194 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | Kumara Sastry, David E. Goldberg, Xavier Llorà: Towards billion-bit optimization via a parallel estimation of distribution algorithm. GECCO 2007: 577-584 |
189 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | Albert Orriols-Puig, Kumara Sastry, David E. Goldberg, Ester Bernadó-Mansilla: Substructural Surrogates for Learning Decomposable Classification Problems. IWLCS 2007: 235-254 |
181 | EE | 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 | EE | David E. Goldberg, Kumara Sastry, Xavier Llorà: Toward routine billion-variable optimization using genetic algorithms. Complexity 12(3): 27-29 (2007) |
179 | EE | 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 | EE | 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 | EE | Naohiro Matsumura, David E. Goldberg, Xavier Llorà: Communication Gap Management for Fertile Community. Soft Comput. 11(8): 791-798 (2007) |
2006 | ||
176 | EE | 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 | EE | Paul Winward, David E. Goldberg: Fluctuating crosstalk, deterministic noise, and GA scalability. GECCO 2006: 1361-1368 |
174 | EE | Tian-Li Yu, David E. Goldberg: Conquering hierarchical difficulty by explicit chunking: substructural chromosome compression. GECCO 2006: 1385-1392 |
173 | EE | Xavier Llorà, Kumara Sastry, Francesc Alías, David E. Goldberg, Michael Welge: Analyzing active interactive genetic algorithms using visual analytics. GECCO 2006: 1417-1418 |
172 | EE | Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wilson, David E. Goldberg: Classifier prediction based on tile coding. GECCO 2006: 1497-1504 |
171 | EE | 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 | EE | 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 | EE | Martin Pelikan, Kumara Sastry, David E. Goldberg: Sporadic model building for efficiency enhancement of hierarchical BOA. GECCO 2006: 405-412 |
168 | EE | Kumara Sastry, Cláudio F. Lima, David E. Goldberg: Evaluation relaxation using substructural information and linear estimation. GECCO 2006: 419-426 |
167 | EE | Martin Pelikan, Kumara Sastry, Martin V. Butz, David E. Goldberg: Hierarchical BOA on random decomposable problems. GECCO 2006: 431-432 |
166 | EE | 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 | EE | Martin Pelikan, Kumara Sastry, Martin V. Butz, David E. Goldberg: Performance of Evolutionary Algorithms on Random Decomposable Problems. PPSN 2006: 788-797 |
164 | EE | Kumara Sastry, Martin Pelikan, David E. Goldberg: Efficiency Enhancement of Estimation of Distribution Algorithms. Scalable Optimization via Probabilistic Modeling 2006: 161-185 |
163 | EE | Martin Pelikan, Kumara Sastry, David E. Goldberg: Multiobjective Estimation of Distribution Algorithms. Scalable Optimization via Probabilistic Modeling 2006: 223-248 |
162 | EE | 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 | EE | 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 | EE | Martin Pelikan, David E. Goldberg: Hierarchical Bayesian Optimization Algorithm. Scalable Optimization via Probabilistic Modeling 2006: 63-90 |
159 | EE | 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 | EE | David E. Goldberg: Little Models, Big Results. Australian Conference on Artificial Intelligence 2005: 4 |
157 | EE | 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 | EE | Kumara Sastry, David E. Goldberg, Martin Pelikan: Limits of scalability of multiobjective estimation of distribution algorithms. Congress on Evolutionary Computation 2005: 2217-2224 |
155 | EE | 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 | EE | 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 | EE | Xavier Llorà, Kumara Sastry, David E. Goldberg: The compact classifier system: scalability analysis and first results. Congress on Evolutionary Computation 2005: 596-603 |
152 | EE | Tian-Li Yu, Kumara Sastry, David E. Goldberg: Linkage learning, overlapping building blocks, and systematic strategy for scalable recombination. GECCO 2005: 1217-1224 |
151 | EE | 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 | EE | Jian-Hung Chen, Shinn-Ying Ho, David E. Goldberg: Quality-time analysis of multi-objective evolutionary algorithms. GECCO 2005: 1455-1462 |
149 | EE | Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wilson, David E. Goldberg: Extending XCSF beyond linear approximation. GECCO 2005: 1827-1834 |
148 | EE | Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wilson, David E. Goldberg: XCS with computed prediction in multistep environments. GECCO 2005: 1859-1866 |
147 | EE | Xavier Llorà, Kumara Sastry, David E. Goldberg: The compact classifier system: motivation, analysis, and first results. GECCO 2005: 1993-1994 |
146 | EE | 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 | EE | Martin Pelikan, Kumara Sastry, David E. Goldberg: Multiobjective hBOA, clustering, and scalability. GECCO 2005: 663-670 |
144 | EE | Kumara Sastry, Hussein A. Abbass, David E. Goldberg, D. D. Johnson: Sub-structural niching in estimation of distribution algorithms. GECCO 2005: 671-678 |
143 | EE | 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 | EE | Xavier Llorà, Kumara Sastry, David E. Goldberg: Binary rule encoding schemes: a study using the compact classifier system. GECCO Workshops 2005: 88-89 |
141 | EE | 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 | EE | Martin V. Butz, David E. Goldberg, Pier Luca Lanzi: Effect of Pure Error-Based Fitness in XCS. IWLCS 2005: 104-114 |
139 | EE | 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 | EE | Xavier Llorà, Kumara Sastry, David E. Goldberg: Binary Rule Encoding Schemes: A Study Using the Compact Classifier System. IWLCS 2005: 40-58 |
137 | EE | Naohiro Matsumura, David E. Goldberg, Xavier Llorà: Communication Gaps in Social Networks. WSTST 2005: 543-552 |
136 | EE | Naohiro Matsumura, David E. Goldberg, Xavier Llorà: Mining directed social network from message board. WWW (Special interest tracks and posters) 2005: 1092-1093 |
135 | EE | Kumara Sastry, Una-May O'Reilly, David E. Goldberg: Population Sizing for Genetic Programming Based Upon Decision Making CoRR abs/cs/0502020: (2005) |
134 | EE | 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 | EE | Kumara Sastry, Hussein A. Abbass, David E. Goldberg: Sub-Structural Niching in Non-Stationary Environments CoRR abs/cs/0502022: (2005) |
132 | EE | 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 | EE | Martin Pelikan, Kumara Sastry, David E. Goldberg: Multiobjective hBOA, Clustering, and Scalability CoRR abs/cs/0502034: (2005) |
130 | EE | Kumara Sastry, Martin Pelikan, David E. Goldberg: Decomposable Problems, Niching, and Scalability of Multiobjective Estimation of Distribution Algorithms CoRR abs/cs/0502057: (2005) |
129 | EE | Ying-Ping Chen, David E. Goldberg: Convergence Time for the Linkage Learning Genetic Algorithm. Evolutionary Computation 13(3): 279-302 (2005) |
128 | EE | Laura A. McLay, David E. Goldberg: Efficient Genetic Algorithms Using Discretization Scheduling. Evolutionary Computation 13(3): 353-385 (2005) |
127 | EE | 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 | EE | 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 | EE | Kumara Sastry, Hussein A. Abbass, David E. Goldberg: Sub-structural Niching in Non-stationary Environments. Australian Conference on Artificial Intelligence 2004: 873-885 |
124 | EE | Kei Ohnishi, Kumara Sastry, Ying-Ping Chen, David E. Goldberg: Inducing Sequentiality Using Grammatical Genetic Codes. GECCO (1) 2004: 1426-1437 |
123 | EE | 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 | EE | Ying-Ping Chen, David E. Goldberg: Introducing Subchromosome Representations to the Linkage Learning Genetic Algorithm. GECCO (1) 2004: 971-982 |
121 | EE | Gerulf K. M. Pedersen, David E. Goldberg: Dynamic Uniform Scaling for Multiobjective Genetic Algorithms. GECCO (2) 2004: 11-23 |
120 | EE | Kumara Sastry, David E. Goldberg: Designing Competent Mutation Operators Via Probabilistic Model Building of Neighborhoods. GECCO (2) 2004: 114-125 |
119 | EE | Kumara Sastry, David E. Goldberg: Let's Get Ready to Rumble: Crossover Versus Mutation Head to Head. GECCO (2) 2004: 126-137 |
118 | EE | 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 | EE | 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 | EE | 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 | EE | Martin V. Butz, David E. Goldberg, Pier Luca Lanzi: Bounding Learning Time in XCS. GECCO (2) 2004: 739-750 |
114 | EE | 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 | EE | 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 | EE | Martin V. Butz, Pier Luca Lanzi, Xavier Llorà, David E. Goldberg: Knowledge Extraction and Problem Structure Identification in XCS. PPSN 2004: 1051-1060 |
111 | EE | Kumara Sastry, David E. Goldberg, Martin Pelikan: Efficiency Enhancement of Probabilistic Model Building Genetic Algorithms CoRR cs.NE/0405062: (2004) |
110 | EE | Kumara Sastry, David E. Goldberg: Let's Get Ready to Rumble: Crossover Versus Mutation Head to Head CoRR cs.NE/0405063: (2004) |
109 | EE | Kumara Sastry, David E. Goldberg: Designing Competent Mutation Operators via Probabilistic Model Building of Neighborhoods CoRR cs.NE/0405064: (2004) |
108 | EE | Kumara Sastry, Martin Pelikan, David E. Goldberg: Efficiency Enhancement of Genetic Algorithms via Building-Block-Wise Fitness Estimation CoRR cs.NE/0405065: (2004) |
107 | EE | Fernando G. Lobo, David E. Goldberg: The parameter-less genetic algorithm in practice. Inf. Sci. 167(1-4): 217-232 (2004) |
2003 | ||
106 | EE | Martin Butz, David E. Goldberg: Generalized State Values in an Anticipatory Learning Classifier System. Anticipatory Behavior in Adaptive Learning Systems 2003: 282-301 |
105 | EE | Xavier Llorà, David E. Goldberg: Wise Breeding GA via Machine Learning Techniques for Function Optimization. GECCO 2003: 1172-1183 |
104 | EE | Martin Pelikan, David E. Goldberg: Hierarchical BOA Solves Ising Spin Glasses and MAXSAT. GECCO 2003: 1271-1282 |
103 | EE | Kumara Sastry, David E. Goldberg: Scalability of Selectorecombinative Genetic Algorithms for Problems with Tight Linkage. GECCO 2003: 1332-1344 |
102 | EE | 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 | EE | 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 | EE | Martin Butz, David E. Goldberg: Bounding the Population Size in XCS to Ensure Reproductive Opportunities. GECCO 2003: 1844-1856 |
99 | EE | Martin Butz, Kumara Sastry, David E. Goldberg: Tournament Selection: Stable Fitness Pressure in XCS. GECCO 2003: 1857-1869 |
98 | EE | 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 | EE | Erick Cantú-Paz, David E. Goldberg: Are Multiple Runs of Genetic Algorithms Better than One? GECCO 2003: 801-812 |
96 | EE | 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 | EE | Ying-Ping Chen, David E. Goldberg: Tightness Time for the Linkage Learning Genetic Algorithm. GECCO 2003: 837-849 |
94 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | Martin Pelikan, Kumara Sastry, David E. Goldberg: Scalability of the Bayesian optimization algorithm. Int. J. Approx. Reasoning 31(3): 221-258 (2002) |
2001 | ||
71 | EE | 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 | EE | 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 | EE | 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 | EE | 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 | EE | 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 |