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Kenneth A. De Jong
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- affiliation: George Mason University, Fairfax, VA, USA
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2020 – today
- 2024
- [c142]Eric O. Scott, Kenneth A. De Jong:
Varying Difficulty of Knowledge Reuse in Benchmarks for Evolutionary Knowledge Transfer. CEC 2024: 1-8 - 2023
- [j28]Kenneth A. De Jong, Emma Hart:
Editorial: Reflecting on Thirty Years of ECJ. Evol. Comput. 31(2): 73-79 (2023) - [j27]Eric O. Scott, Mark Coletti, Catherine D. Schuman, Bill Kay, Shruti R. Kulkarni, Maryam Parsa
, Chathika Gunaratne, Kenneth A. De Jong:
Avoiding excess computation in asynchronous evolutionary algorithms. Expert Syst. J. Knowl. Eng. 40(5) (2023) - [j26]Ahmed Bin Zaman
, Toki Tahmid Inan
, Kenneth A. De Jong
, Amarda Shehu
:
Adaptive Stochastic Optimization to Improve Protein Conformation Sampling. IEEE ACM Trans. Comput. Biol. Bioinform. 20(5): 2759-2771 (2023) - [c141]Eric O. Scott
, Kenneth A. De Jong
:
First Complexity Results for Evolutionary Knowledge Transfer. FOGA 2023: 140-151 - [c140]Kenneth A. De Jong
:
Evolutionary Computation Evolving. GECCO 2023: 1 - [c139]Eric O. Scott
, Kenneth A. De Jong
:
Initialization Matters for Asynchronous Steady-State Evolutionary Algorithms. GECCO Companion 2023: 1570-1578 - 2022
- [j25]Abhishek Gupta
, Yew-Soon Ong
, Kenneth A. De Jong
, Mengjie Zhang
:
Guest Editorial Special Issue on Multitask Evolutionary Computation. IEEE Trans. Evol. Comput. 26(2): 202-205 (2022) - 2021
- [c138]Xinyun Zou
, Eric O. Scott, Alexander B. Johnson, Kexin Chen
, Douglas A. Nitz, Kenneth A. De Jong, Jeffrey L. Krichmar:
Neuroevolution of a recurrent neural network for spatial and working memory in a simulated robotic environment. GECCO Companion 2021: 289-290 - [c137]Kexin Chen
, Alexander B. Johnson, Eric O. Scott, Xinyun Zou
, Kenneth A. De Jong, Douglas A. Nitz, Jeffrey L. Krichmar:
Differential Spatial Representations in Hippocampal CA1 and Subiculum Emerge in Evolved Spiking Neural Networks. IJCNN 2021: 1-8 - [c136]Eric O. Scott, Mark Coletti, Catherine D. Schuman
, Bill Kay, Shruti R. Kulkarni, Maryam Parsa
, Kenneth A. De Jong:
Avoiding Excess Computation in Asynchronous Evolutionary Algorithms. UKCI 2021: 71-82 - [d1]Ahmed Bin Zaman, Toki Tahmid Inan, Kenneth A. De Jong, Amarda Shehu:
Adaptive Conformation Sampling Dataset Zaman_TCBB21. IEEE DataPort, 2021 - [i3]Xinyun Zou
, Eric O. Scott, Alexander B. Johnson, Kexin Chen, Douglas A. Nitz, Kenneth A. De Jong, Jeffrey L. Krichmar:
Neuroevolution of a Recurrent Neural Network for Spatial and Working Memory in a Simulated Robotic Environment. CoRR abs/2102.12638 (2021) - 2020
- [c135]Kenneth A. De Jong:
Evolutionary computation: a unified approach. GECCO Companion 2020: 327-342
2010 – 2019
- 2019
- [c134]Eric O. Scott, Kenneth A. De Jong:
Automating Knowledge Transfer with Multi-Task Optimization. CEC 2019: 2252-2259 - [c133]Kenneth A. De Jong:
Evolutionary computation: a unified approach. GECCO (Companion) 2019: 507-522 - [c132]Ahmed Bin Zaman, Kenneth A. De Jong, Amarda Shehu:
Using subpopulation EAs to map molecular structure landscapes. GECCO 2019: 960-967 - [p4]Uday Kamath, Carlotta Domeniconi, Amarda Shehu, Kenneth A. De Jong:
EML: A Scalable, Transparent Meta-Learning Paradigm for Big Data Applications. Innovations in Big Data Mining and Embedded Knowledge 2019: 35-59 - 2018
- [j24]Uday Kamath, Carlotta Domeniconi, Kenneth A. De Jong:
Theoretical and Empirical Analysis of a Spatial EA Parallel Boosting Algorithm. Evol. Comput. 26(1) (2018) - [j23]Siva Venkadesh
, Alexander O. Komendantov, Stanislav Listopad, Eric O. Scott, Kenneth A. De Jong, Jeffrey L. Krichmar, Giorgio A. Ascoli:
Evolving Simple Models of Diverse Intrinsic Dynamics in Hippocampal Neuron Types. Frontiers Neuroinformatics 12: 8 (2018) - [j22]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu
:
From Optimization to Mapping: An Evolutionary Algorithm for Protein Energy Landscapes. IEEE ACM Trans. Comput. Biol. Bioinform. 15(3): 719-731 (2018) - [c131]Eric O. Scott, Kenneth A. De Jong:
Toward learning neural network encodings for continuous optimization problems. GECCO (Companion) 2018: 123-124 - [c130]Kenneth A. De Jong:
Evolutionary computation: a unified approach. GECCO (Companion) 2018: 373-388 - 2017
- [c129]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
Evolving Conformation Paths to Model Protein Structural Transitions. BCB 2017: 673-678 - [c128]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
Modeling protein structural transitions as a multiobjective optimization problem. CIBCB 2017: 1-8 - [c127]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
Evolutionary search for paths on protein energy landscapes. GECCO (Companion) 2017: 77-78 - [c126]Eric O. Scott, Kenneth A. De Jong:
Multitask evolution with cartesian genetic programming. GECCO (Companion) 2017: 255-256 - [c125]Kenneth A. De Jong:
Evolutionary computation: a unified approach. GECCO (Companion) 2017: 373-388 - [c124]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
An evolutionary algorithm to model structural excursions of a protein. GECCO (Companion) 2017: 1669-1673 - [i2]Eric O. Scott, Kenneth A. De Jong:
Multitask Evolution with Cartesian Genetic Programming. CoRR abs/1702.02217 (2017) - 2016
- [c123]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
A Novel EA-based Memetic Approach for Efficiently Mapping Complex Fitness Landscapes. GECCO 2016: 85-92 - [c122]Kenneth A. De Jong:
Evolutionary Computation: A Unified Approach. GECCO (Companion) 2016: 185-199 - [c121]Eric O. Scott, Kenneth A. De Jong:
Evaluation-Time Bias in Quasi-Generational and Steady-State Asynchronous Evolutionary Algorithms. GECCO 2016: 845-852 - [c120]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
Path-based Guidance of an Evolutionary Algorithm in Mapping a Fitness Landscape and its Connectivity. GECCO (Companion) 2016: 1293-1298 - [c119]Emily L. Rounds, Eric O. Scott, Andrew S. Alexander, Kenneth A. De Jong, Douglas A. Nitz, Jeffrey L. Krichmar
:
An Evolutionary Framework for Replicating Neurophysiological Data with Spiking Neural Networks. PPSN 2016: 537-547 - [c118]Eric O. Scott, Kenneth A. De Jong:
Landscape Features for Computationally Expensive Evaluation Functions: Revisiting the Problem of Noise. PPSN 2016: 952-961 - 2015
- [c117]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
Evolutionary search strategies for efficient sample-based representations of multiple-basin protein energy landscapes. BIBM 2015: 13-20 - [c116]Alexei V. Samsonovich
, Anastasia Kitsantas, Ellen O'Brien, Kenneth A. De Jong:
Cognitive Processes in Preparation for Problem Solving. BICA 2015: 235-247 - [c115]Eric O. Scott, Kenneth A. De Jong:
Understanding Simple Asynchronous Evolutionary Algorithms. FOGA 2015: 85-98 - [c114]Kenneth A. De Jong:
Evolutionary Computation: A Unified Approach. GECCO (Companion) 2015: 21-35 - [c113]Rudy Clausen, Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
Evolution Strategies for Exploring Protein Energy Landscapes. GECCO 2015: 217-224 - [c112]Amarda Shehu, Kenneth A. De Jong:
Evolutionary Algorithms for Protein Structure Modeling. GECCO (Companion) 2015: 533-545 - [c111]Emmanuel Sapin, Kenneth A. De Jong, Amarda Shehu:
Mapping Multiple Minima in Protein Energy Landscapes with Evolutionary Algorithms. GECCO (Companion) 2015: 923-927 - [c110]Eric O. Scott, Kenneth A. De Jong:
Evaluation-Time Bias in Asynchronous Evolutionary Algorithms. GECCO (Companion) 2015: 1209-1212 - [c109]Kenneth A. De Jong:
Co-Evolutionary Algorithms: A Useful Computational Abstraction? SSBSE 2015: 3-11 - [i1]Uday Kamath, Carlotta Domeniconi, Kenneth A. De Jong:
Theoretical and Empirical Analysis of a Parallel Boosting Algorithm. CoRR abs/1508.01549 (2015) - 2014
- [c108]Kenneth A. De Jong:
Evolutionary computation: a unified approach. GECCO (Companion) 2014: 281-296 - [c107]Uday Kamath, Jessica Lin, Kenneth A. De Jong:
SAX-EFG: an evolutionary feature generation framework for time series classification. GECCO 2014: 533-540 - [c106]Amarda Shehu
, Kenneth A. De Jong:
Evolutionary search algorithms for protein modeling: from de novo structure prediction to comprehensive maps of functionally-relevant structures of protein chains and assemblies. GECCO (Companion) 2014: 839-856 - 2013
- [c105]Brian S. Olson, Kenneth A. De Jong, Amarda Shehu
:
Off-lattice protein structure prediction with homologous crossover. GECCO 2013: 287-294 - [c104]Kenneth A. De Jong:
Evolutionary computation: a unified approach. GECCO (Companion) 2013: 293-306 - [c103]Uday Kamath, Carlotta Domeniconi, Kenneth A. De Jong:
An analysis of a spatial EA parallel boosting algorithm. GECCO 2013: 1053-1060 - [e3]Frank Neumann, Kenneth A. De Jong:
Foundations of Genetic Algorithms XII, FOGA '13, Adelaide, SA, Australia, January 16-20, 2013. ACM 2013, ISBN 978-1-4503-1990-4 [contents] - 2012
- [j21]Claudio Cioffi-Revilla, Kenneth A. De Jong, Jeffrey K. Bassett:
Evolutionary computation and agent-based modeling: biologically-inspired approaches for understanding complex social systems. Comput. Math. Organ. Theory 18(3): 356-373 (2012) - [j20]Uday Kamath, Jack Compton, Rezarta Islamaj Dogan
, Kenneth A. De Jong, Amarda Shehu
:
An Evolutionary Algorithm Approach for Feature Generation from Sequence Data and Its Application to DNA Splice Site Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. 9(5): 1387-1398 (2012) - [c102]Jeffrey K. Bassett, Uday Kamath, Kenneth A. De Jong:
A new methodology for the GP theory toolbox. GECCO 2012: 719-726 - [c101]Kenneth A. De Jong:
Evolutionary computation: a unified approach. GECCO (Companion) 2012: 737-750 - [c100]James McDermott, David Robert White, Sean Luke, Luca Manzoni
, Mauro Castelli
, Leonardo Vanneschi
, Wojciech Jaskowski
, Krzysztof Krawiec
, Robin Harper, Kenneth A. De Jong, Una-May O'Reilly:
Genetic programming needs better benchmarks. GECCO 2012: 791-798 - [c99]Yan Guo, Kenneth A. De Jong, Fujiang Liu, Xiaopan Wang, Chan Li:
A Comparison of Artificial Neural Networks and Support Vector Machines on Land Cover Classification. ISICA 2012: 531-539 - [c98]Uday Kamath, Johan Kaers, Amarda Shehu
, Kenneth A. De Jong:
A Spatial EA Framework for Parallelizing Machine Learning Methods. PPSN (1) 2012: 206-215 - [p3]Christian Blum
, Raymond Chiong
, Maurice Clerc, Kenneth A. De Jong, Zbigniew Michalewicz
, Ferrante Neri
, Thomas Weise:
Evolutionary Optimization. Variants of Evolutionary Algorithms for Real-World Applications 2012: 1-29 - [p2]Kenneth A. De Jong:
Generalized Evolutionary Algorithms. Handbook of Natural Computing 2012: 625-635 - 2011
- [j19]Uday Kamath, Amarda Shehu
, Kenneth A. De Jong:
A Two-Stage Evolutionary Approach for Effective Classification of hypersensitive DNA Sequences. J. Bioinform. Comput. Biol. 9(3): 399-413 (2011) - [c97]Uday Kamath, Kenneth A. De Jong, Amarda Shehu
:
An evolutionary-based approach for feature generation: Eukaryotic promoter recognition. IEEE Congress on Evolutionary Computation 2011: 277-284 - [c96]Mohamad M. Awad
, Kenneth A. De Jong:
Optimization of spectral signatures selection using multi-objective genetic algorithms. IEEE Congress on Evolutionary Computation 2011: 1620-1627 - [c95]Alexei V. Samsonovich, Anastasia Kitsantas, Ellen O'Brien, Kenneth A. De Jong:
Detecting Student Metacognition and Learning in Problem Solving with Biologically Inspired Cognitive Architectures. CogSci 2011 - [c94]Jeffrey Kermes Bassett, Kenneth A. De Jong:
Using multivariate quantitative genetics theory to assist in EA customization. FOGA 2011: 219-230 - [c93]Kenneth A. De Jong:
Evolutionary computation: a unified approach. GECCO (Companion) 2011: 899-912 - 2010
- [c92]Alexei V. Samsonovich, Kenneth A. De Jong, Anastasia Kitsantas, Ellen O'Brien:
Assessment of the Critical Components of a Transformative Self-Regulated Learning Assistant. AAAI Fall Symposium: Cognitive and Metacognitive Educational Systems 2010 - [c91]Michael Q. Kalish, Alexei V. Samsonovich
, Mark Coletti, Kenneth A. De Jong:
Assessing the Role of Metacognition in GMU BICA. BICA 2010: 72-77 - [c90]Uday Kamath, Amarda Shehu
, Kenneth A. De Jong:
Feature and Kernel Evolution for Recognition of Hypersensitive Sites in DNA Sequences. BIONETICS 2010: 213-228 - [c89]Uday Kamath, Amarda Shehu
, Kenneth A. De Jong:
Using evolutionary computation to improve SVM classification. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c88]Uday Kamath, Kenneth A. De Jong, Amarda Shehu
:
Selecting predictive features for recognition of hypersensitive sites of regulatory genomic sequences with an evolutionary algorithm. GECCO 2010: 179-186 - [c87]Kenneth A. De Jong:
Evolutionary computation: a unified approach. GECCO (Companion) 2010: 2289-2302 - [c86]Kenneth A. De Jong:
Evolutionary computation: challenges for the 21st century. BADS@ICAC 2010: 17-18
2000 – 2009
- 2009
- [c85]Elena Popovici, Kenneth A. De Jong:
Monotonicity versus performance in co-optimization. FOGA 2009: 151-170 - [c84]Jeffrey K. Bassett, Mark Coletti, Kenneth A. De Jong:
The relationship between evolvability and bloat. GECCO 2009: 1899-1900 - [c83]Kenneth A. De Jong:
A unified approach to Evolutionary Computation. GECCO (Companion) 2009: 2811-2824 - 2008
- [j18]Zbigniew Skolicki, Tomasz Arciszewski, M. H. Houck, Kenneth A. De Jong:
Co-evolution of terrorist and security scenarios for water distribution systems. Adv. Eng. Softw. 39(10): 801-811 (2008) - [j17]Kenneth A. De Jong:
Evolving intelligent agents: A 50 year quest. IEEE Comput. Intell. Mag. 3(1): 12-17 (2008) - [c82]Alexei V. Samsonovich, Kenneth A. De Jong, Anastasia Kitsantas, Erin E. Peters, Nada Dabbagh, M. Layne Kalbfleisch:
Cognitive Constructor: An Intelligent Tutoring System Based on a Biologically Inspired Cognitive Architecture (BICA). AGI 2008: 311-325 - [c81]Kenneth A. De Jong:
Evolutionary computation: a unified approach. GECCO (Companion) 2008: 2245-2258 - [c80]Zohreh Nazeri, Daniel Barbará, Kenneth A. De Jong, George L. Donohue, Lance Sherry
:
Contrast-Set Mining of Aircraft Accidents and Incidents. ICDM 2008: 313-322 - 2007
- [c79]Zbigniew Skolicki, Kenneth A. De Jong:
The importance of a two-level perspective for island model design. IEEE Congress on Evolutionary Computation 2007: 4623-4630 - [c78]Kenneth A. De Jong:
Evolutionary computation: a unified approach. GECCO (Companion) 2007: 3158-3171 - [p1]Kenneth A. De Jong:
Parameter Setting in EAs: a 30 Year Perspective. Parameter Setting in Evolutionary Algorithms 2007: 1-18 - 2006
- [b1]Kenneth A. De Jong:
Evolutionary computation - a unified approach. MIT Press 2006, ISBN 978-0-262-04194-2, pp. I-IX, 1-256 - [j16]Elena Popovici, Kenneth A. De Jong:
The dynamics of the best individuals in co-evolution. Nat. Comput. 5(3): 229-255 (2006) - [c77]Elena Popovici, Kenneth A. De Jong:
Sequential versus Parallel Cooperative Coevolutionary Algorithms for Optimization. IEEE Congress on Evolutionary Computation 2006: 1610-1617 - [c76]Elena Popovici, Kenneth A. De Jong:
The effects of interaction frequency on the optimization performance of cooperative coevolution. GECCO 2006: 353-360 - [c75]Alexei V. Samsonovich, Giorgio A. Ascoli, Kenneth A. De Jong:
Computational Assessment of the 'Magic' of Human Cognition. IJCNN 2006: 443-450 - 2005
- [j15]Thomas Jansen
, Kenneth A. De Jong, Ingo Wegener:
On the Choice of the Offspring Population Size in Evolutionary Algorithms. Evol. Comput. 13(4): 413-440 (2005) - [j14]Rafal Kicinger, Tomasz Arciszewski, Kenneth A. De Jong:
Emergent Designer: An Integrated Research and Design Support Tool Based on Models of Complex Systems. J. Inf. Technol. Constr. 10: 329-347 (2005) - [c74]Elena Popovici, Kenneth A. De Jong:
A Dynamical Systems Analysis of Collaboration Methods in Cooperative Co-evolution. AAAI Fall Symposium: Coevolutionary and Coadaptive Systems 2005: 26-34 - [c73]Elena Popovici, Kenneth A. De Jong:
Relationships between internal and external metrics in co-evolution. Congress on Evolutionary Computation 2005: 2800-2807 - [c72]Neera P. Sood, Ashley G. Williams, Kenneth A. De Jong:
Evaluating the XCS learning classifier system in competitive simultaneous learning environments. GECCO Workshops 2005: 112-118 - [c71]Elena Popovici, Kenneth A. De Jong:
Understanding cooperative co-evolutionary dynamics via simple fitness landscapes. GECCO 2005: 507-514 - [c70]Zbigniew Skolicki, Kenneth A. De Jong:
The influence of migration sizes and intervals on island models. GECCO 2005: 1295-1302 - [c69]Alexei V. Samsonovich
, Kenneth A. De Jong:
Pricing the 'free lunch' of meta-evolution. GECCO 2005: 1355-1362 - [c68]Jeffrey K. Bassett, Mitchell A. Potter, Kenneth A. De Jong:
Applying price's equation to survival selection. GECCO 2005: 1371-1378 - [c67]Rafal Kicinger, Tomasz Arciszewski, Kenneth A. De Jong:
Parameterized versus generative representations in structural design: an empirical comparison. GECCO 2005: 2007-2014 - [e2]Alden H. Wright, Michael D. Vose, Kenneth A. De Jong, Lothar M. Schmitt:
Foundations of Genetic Algorithms, 8th International Workshop, FOGA 2005, Aizu-Wakamatsu City, Japan, January 5-9, 2005, Revised Selected Papers. Lecture Notes in Computer Science 3469, Springer 2005, ISBN 3-540-27237-2 [contents] - 2004
- [c66]Elena Popovici, Kenneth A. De Jong:
Understanding Competitive Co-Evolutionary Dynamics via Fitness Landscapes. AAAI Technical Report (2) 2004: 118- - [c65]Rafal Kicinger, Tomasz Arciszewski, Kenneth A. De Jong:
Morphogenesis and structural design: cellular automata representations of steel structures in tall buildings. IEEE Congress on Evolutionary Computation 2004: 411-418 - [c64]Jeffrey K. Bassett, Mitchell A. Potter, Kenneth A. De Jong:
Looking Under the EA Hood with Price's Equation. GECCO (1) 2004: 914-922 - [c63]Adrian Grajdeanu, Kenneth A. De Jong:
Improving the Locality Properties of Binary Representations. GECCO (1) 2004: 1186-1196 - [c62]Alexei V. Samsonovich, Kenneth A. De Jong:
A General-Purpose Computational Model of the Conscious Mind. ICCM 2004: 382-383 - [c61]Zbigniew Skolicki, Kenneth A. De Jong:
Improving Evolutionary Algorithms with Multi-representation Island Models. PPSN 2004: 420-429 - 2003
- [c60]Mitchell A. Potter, Jeffrey K. Bassett, Kenneth A. De Jong:
Visualizing evolvability with Price's equation. IEEE Congress on Evolutionary Computation 2003: 2785-2790 - [c59]Elena Popovici, Kenneth A. De Jong:
Understanding EA Dynamics via Population Fitness Distributions. GECCO 2003: 1604-1605 - [c58]William G. Kennedy, Kenneth A. De Jong:
Characteristics of Long-term Learning in Soar and its Application to the Utility Problem. ICML 2003: 337-344 - [e1]Kenneth A. De Jong, Riccardo Poli, Jonathan E. Rowe:
Proceedings of the Seventh Workshop on Foundations of Genetic Algorithms, Torremolinos, Spain, September 2-4, 2002. Morgan Kaufmann 2003, ISBN 0122081552 [contents] - 2002
- [c57]Donald Sofge, Kenneth A. De Jong, Alan C. Schultz:
A blended population approach to cooperative coevolution for decomposition of complex problems. IEEE Congress on Evolutionary Computation 2002: 413-418 - [c56]R. Paul Wiegand, William C. Liles, Kenneth A. De Jong:
Analyzing cooperative coevolution with evolutionary game theory. IEEE Congress on Evolutionary Computation 2002: 1600-1605 - [c55]Donald Sofge, Alan C. Schultz, Kenneth A. De Jong:
Evolutionary Computational Approaches to Solving the Multiple Traveling Salesman Problem Using a Neighborhood Attractor Schema. EvoWorkshops 2002: 153-162 - [c54]Kenneth A. De Jong, Riccardo Poli, Jonathan E. Rowe:
Editorial Introduction. FOGA 2002: 1-8 - [c53]R. Paul Wiegand, William C. Liles, Kenneth A. De Jong:
Modeling Variation in Cooperative Coevolution Using Evolutionary Game Theory. FOGA 2002: 203-220 - [c52]Thomas Jansen, Kenneth A. De Jong:
An Analysis Of The Role Of Offspring Population Size In EAs. GECCO 2002: 238-246 - [c51]R. Paul Wiegand, William C. Liles, Kenneth A. De Jong:
The Effects of Representational Bias on Collaboration Methods in Cooperative Coevolution. PPSN 2002: 257-270 - 2001
- [j13]Alaa F. Sheta
, Kenneth A. De Jong:
Time-series forecasting using GA-tuned radial basis functions. Inf. Sci. 133(3-4): 221-228 (2001) - [c50]Ronald W. Morrison, Kenneth A. De Jong:
Measurement of Population Diversity. Artificial Evolution 2001: 31-41 - 2000
- [j12]Mitchell A. Potter, Kenneth A. De Jong:
Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents. Evol. Comput. 8(1): 1-29 (2000) - [j11]Krzysztof Murawski, Tomasz Arciszewski, Kenneth A. De Jong:
Evolutionary Computation in Structural Design. Eng. Comput. 16(3-4): 275-286 (2000) - [c49]Jean-Michel Claverie, Kenneth A. De Jong, Alaa F. Sheta:
Robust nonlinear control design using competitive coevolution. CEC 2000: 403-409 - [c48]Ronald W. Morrison, Kenneth A. De Jong:
Triggered hypermutation revisited. CEC 2000: 1025-1032 - [c47]Rida E. Moustafa, Kenneth A. De Jong, Edward J. Wegman:
A GA-Based Method for Function Approximation Using Adaptive Interpolation. GECCO 2000: 378 - [c46]Jeffrey K. Bassett, Kenneth A. De Jong:
Evolving Behaviors for Cooperating Agents. ISMIS 2000: 157-165
1990 – 1999
- 1999
- [j10]Kenneth A. De Jong:
Evolutionary Computation for Discovery. Commun. ACM 42(11): 51-53 (1999) - [c45]Annie S. Wu, Kenneth A. De Jong:
An examination of building block dynamics in different representations. CEC 1999: 715-721 - [c44]Annie S. Wu, Kenneth A. De Jong, Donald S. Burke, John J. Grefenstette, Connie Loggia Ramsey:
Visual analysis of evolutionary algorithms. CEC 1999: 1419-1425 - [c43]Ronald W. Morrison, Kenneth A. De Jong:
A test problem generator for non-stationary environments. CEC 1999: 2047-2053 - [c42]William C. Liles, Kenneth A. De Jong:
The usefulness of tag bits in changing environments. CEC 1999: 2054-2062 - [c41]Kenneth A. De Jong:
Evolutionary Computation: Where We Are and where We're Headed. Fuzzy Days 1999: 230-231 - [c40]Kenneth A. De Jong:
Evolving in a Changing World. ISMIS 1999: 512-519 - 1998
- [j9]Donald S. Burke, Kenneth A. De Jong, John J. Grefenstette, Connie Loggia Ramsey, Annie S. Wu:
Putting More Genetics into Genetic Algorithms. Evol. Comput. 6(4): 387-410 (1998) - [j8]Haleh Vafaie, Kenneth A. De Jong:
Feature Space Transformation Using Genetic Algorithms. IEEE Intell. Syst. 13(2): 57-65 (1998) - [j7]Kenneth A. De Jong:
Evolutionary Computation: Where We Are and Where We're Headed. Fundam. Informaticae 35(1-4): 247-259 (1998) - [c39]Kenneth A. De Jong:
Learning in Agent-Oriented Worlds (Abstract). ECML 1998: 3 - [c38]William M. Spears, Kenneth A. De Jong:
Dining with GAs: Operator Lunch Theorems. FOGA 1998: 85-101 - [c37]Connie Loggia Ramsey, Kenneth A. De Jong, John J. Grefenstette, Annie S. Wu, Donald S. Burke:
Genome Length as an Evolutionary Self-adaptation. PPSN 1998: 345-356 - [c36]Mitchell A. Potter, Kenneth A. De Jong:
The Coevolution of Antibodies for Concept Learning. PPSN 1998: 530-539 - 1997
- [c35]Jayshree Sarma, Kenneth A. De Jong:
An Analysis of Local Selection Algorithms in a Spatially Structured Evolutionary Algorithm. ICGA 1997: 181-187 - [c34]Kenneth A. De Jong, Mitchell A. Potter, William M. Spears:
Using Problem Generators to Explore the Effects of Epistasis. ICGA 1997: 338-345 - 1996
- [j6]Jerzy W. Bala, Kenneth A. De Jong, Jeffrey Huang, Haleh Vafaie, Harry Wechsler:
Using Learning to Facilitate the Evolution of Features for Recognizing Visual Concepts. Evol. Comput. 4(3): 297-311 (1996) - [c33]William M. Spears, Kenneth A. De Jong:
Analyzing GAs Using Markov Models with Semantically Ordered and Lumped States. FOGA 1996: 85-100 - [c32]Jerzy W. Bala, Kenneth A. De Jong, Jeffrey Huang, Haleh Vafaie, Harry Wechsler:
Visual routine for eye detection using hybrid genetic architectures. ICPR 1996: 606-610 - [c31]Kenneth A. De Jong:
On Evolving Intelligence . ISMIS 1996: 149-157 - [c30]Jayshree Sarma, Kenneth A. De Jong:
An Analysis of the Effects of Neighborhood Size and Shape on Local Selection Algorithms. PPSN 1996: 236-244 - 1995
- [c29]Kenneth A. De Jong, Mitchell A. Potter:
Evolving Complex Structures via Cooperative Coevolution. Evolutionary Programming 1995: 307-317 - [c28]Kenneth A. De Jong, Jayshree Sarma:
On Decentralizing Selection Algorithms. ICGA 1995: 17-23 - [c27]Mitchell A. Potter, Kenneth A. De Jong, John J. Grefenstette:
A Coevolutionary Approach to Learning Sequential Decision Rules. ICGA 1995: 366-372 - [c26]Haleh Vafaie, Kenneth A. De Jong:
Genetic algorithms as a tool for restructuring feature space representations. ICTAI 1995: 8-11 - [c25]Pawel A. Stefanski, H. Hadon Nash, Kenneth A. De Jong:
An object-oriented toolkit for evolutionary algorithms. ICTAI 1995: 156-163 - [c24]Jerzy W. Bala, Jeffrey Huang, Haleh Vafaie, Kenneth A. De Jong, Harry Wechsler:
Hybrid Learning Using Genetic Algorithms and Decision Trees for Pattern Classification. IJCAI (1) 1995: 719-724 - 1994
- [c23]Kenneth A. De Jong, William M. Spears, Diana F. Gordon:
Using Markov Chains to Analyze GAFOs. FOGA 1994: 115-137 - [c22]Kenneth A. De Jong:
An Introduction to Evolutionary Computation and Its Applications. Fuzzy Days 1994: 323-331 - [c21]Mitchell A. Potter, Kenneth A. De Jong:
A Cooperative Coevolutionary Approach to Function Optimization. PPSN 1994: 249-257 - 1993
- [j5]Alan C. Schultz, John J. Grefenstette, Kenneth A. De Jong:
Test and Evaluation by Genetic Algorithms. IEEE Expert 8(5): 9-14 (1993) - [j4]Kenneth A. De Jong, William M. Spears, Diana F. Gordon:
Using Genetic Algorithms for Concept Learning. Mach. Learn. 13: 161-188 (1993) - [j3]Benjamin W. Wah, Thomas S. Huang, Aravind K. Joshi, Dan I. Moldovan, Yiannis Aloimonos, Ruzena Bajcsy, Dana H. Ballard, Doug DeGroot, Kenneth A. De Jong, Charles R. Dyer, Scott E. Fahlman, Ralph Grishman, Lynette Hirschman, Richard E. Korf, Stephen E. Levinson, Daniel P. Miranker, N. H. Morgan, Sergei Nirenburg, Tomaso A. Poggio, Edward M. Riseman, Craig Stanfil, Salvatore J. Stolfo, Steven L. Tanimoto, Charles C. Weems:
Report on Workshop on High Performance Computing and Communications for Grand Challenge Applications: Computer Vision, Speech and Natural Language Processing, and Artificial Intelligence. IEEE Trans. Knowl. Data Eng. 5(1): 138-154 (1993) - [c20]William M. Spears, Kenneth A. De Jong, Thomas Bäck, David B. Fogel, Hugo de Garis:
An Overview of Evolutionary Computation. ECML 1993: 442-459 - [c19]Kenneth A. De Jong, William M. Spears:
On the State of Evolutionary Computation. ICGA 1993: 618-625 - [c18]Haleh Vafaie, Kenneth A. De Jong:
Robust Feature Selection Algorithms. ICTAI 1993: 356-363 - 1992
- [j2]Kenneth A. De Jong, William M. Spears:
A Formal Analysis of the Role of Multi-Point Crossover in Genetic Algorithms. Ann. Math. Artif. Intell. 5(1): 1-26 (1992) - [c17]Kenneth A. De Jong:
Genetic Algorithms are NOT Function Optimizers. FOGA 1992: 5-17 - [c16]Kenneth A. De Jong, Jayshree Sarma:
Generation Gaps Revisited. FOGA 1992: 19-28 - [c15]Haleh Vafaie, Kenneth A. De Jong:
Genetic Algorithms as a Tool for Feature Selection in Machine Learning. ICTAI 1992: 200-203 - [c14]Kenneth A. De Jong:
Are Genetic Algorithms Function Optimizers? PPSN 1992: 3-14 - 1991
- [c13]William M. Spears, Kenneth A. De Jong:
On the Virtues of Parameterised Uniform Crossover. ICGA 1991: 230-236 - [c12]Kenneth A. De Jong, William M. Spears:
Learning Concept Classification Rules Using Genetic Algorithms. IJCAI 1991: 651-657 - [c11]Jerzy W. Bala, Kenneth A. De Jong, Peter Pachowicz:
Using Genetic Algorithms to Improve the Performance of Classification Rules Produced by Symolic Inductive Methods. ISMIS 1991: 286-295 - 1990
- [c10]William M. Spears, Kenneth A. De Jong:
An Analysis of Multi-Point Crossover. FOGA 1990: 301-315 - [c9]William M. Spears, Kenneth A. De Jong:
Using genetic algorithms for supervised concept learning. TAI 1990: 335-341 - [c8]Kejitan Dontas, Kenneth A. De Jong:
Discovery of maximal distance codes using genetic algorithms. TAI 1990: 805-811 - [c7]Jerzy W. Bala, Kenneth A. De Jong:
Generation of feature detectors for texture discrimination by genetic search. TAI 1990: 812-818 - [c6]Kenneth A. De Jong, William M. Spears:
An Analysis of the Interacting Roles of Population Size and Crossover in Genetic Algorithms. PPSN 1990: 38-47
1980 – 1989
- 1989
- [c5]Kenneth A. De Jong, William M. Spears:
Using Genetic Algorithms to Solve NP-Complete Problems. ICGA 1989: 124-132 - 1988
- [j1]Kenneth A. De Jong:
Learning with Genetic Algorithms: An Overview. Mach. Learn. 3: 121-138 (1988) - [c4]Kenneth A. De Jong, Alan C. Schultz:
Using Experience-Based Learning in Game Playing. ML 1988: 284-290 - 1987
- [c3]Kenneth A. De Jong:
On Using Genetic Algorithms to Search Program Spaces. ICGA 1987: 210-216 - 1985
- [c2]Kenneth A. De Jong:
Genetic algorithms: A 10 Year Perspective. ICGA 1985: 169-177
1970 – 1979
- 1979
- [c1]William M. Conner, Kenneth A. De Jong:
The academic/industry gap in systems programming and operating systems. SIGCSE 1979: 118-126
Coauthor Index
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