David E. Goldberg

Dirk Thierens, David E. Goldberg, D. Goldberg, 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

Efficient Genetic Algorithms Using Discretization Scheduling

David E. Goldberg, Laura A. McLay, D. Goldberg, 2005, Evolutionary Computation.

Genetic Algorithms and Computer-Assisted Music Composition

David E. Goldberg, Andrew Horner, D. Goldberg, 1991, ICMC.

The gambler''s ruin problem

David E. Goldberg, Erick Cantú-Paz, Brad L. Miller, 1997 .

Population sizing for entropy-based model building in discrete estimation of distribution algorithms

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2007, GECCO '07.

The innovation pump: supporting creative processes in collaborative engineering

Xavier Llorà, David E. Goldberg, D. Goldberg, 2009 .

A Comparative Analysis of Selection Schemes Used in Genetic Algorithms

Kalyanmoy Deb, David E. Goldberg, D. Goldberg, 1990, FOGA.

Scalability of Selectorecombinative Genetic Algorithms for Problems with Tight Linkage

David E. Goldberg, Kumara Sastry, D. Goldberg, 2003, GECCO.

Probability-Enhanced Predictions in the Anticipatory Classifier System

Martin V. Butz, David E. Goldberg, Wolfgang Stolzmann, 2000, IWLCS.

Inverse kinematics of redundant robots using genetic algorithms

David E. Goldberg, Joey K. Parker, Ahmad R. Khoogar, 1989, Proceedings, 1989 International Conference on Robotics and Automation.

Efficiency enhancement of genetic algorithms via building-block-wise fitness estimation

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

Probabilistic Crowding: Deterministic Crowding with Probabilistic Replacement

David E. Goldberg, Ole J. Mengshoel, D. Goldberg, 1999 .

Genetic Programming 1998: Proceedings of the Third Annual Conference

Hitoshi Iba, David E. Goldberg, Kalyanmoy Deb, 1999, IEEE Trans. Evol. Comput..

Combining competent crossover and mutation operators: a probabilistic model building approach

David E. Goldberg, Kumara Sastry, Cláudio F. Lima, 2005, GECCO '05.

A hydroinformatician's approach to computational innovation and the design of genetic algorithms

David E. Goldberg, D. Goldberg, 2000 .

Linkage Identification by Non-monotonicity Detection for Overlapping Functions

David E. Goldberg, Masaharu Munetomo, D. Goldberg, 1999, Evolutionary Computation.

Real-Coded Bayesian Optimization Algorithm: Bringing the Strength of BOA into the Continuous World

David E. Goldberg, Chang Wook Ahn, R. S. Ramakrishna, 2004, GECCO.

Loopy Substructural Local Search for the Bayesian Optimization Algorithm

David E. Goldberg, Martin Pelikan, Cláudio F. Lima, 2009, SLS.

Multiple-objective Bayesian Optimization Algorithm

David E. Goldberg, Martin Pelikan, Nazan Khan, 2002, GECCO.

Introducing Start Expression Genes to the Linkage Learning Genetic Algorithm

David E. Goldberg, Ying-Ping Chen, D. Goldberg, 2002, PPSN.

The compact genetic algorithm

David E. Goldberg, Fernando G. Lobo, Georges R. Harik, 1999, IEEE Trans. Evol. Comput..

Is Engineering Philosophically Weak

David E. Goldberg, D. Goldberg, 2013 .

Analyzing active interactive genetic algorithms using visual analytics

Xavier Llorà, David E. Goldberg, Kumara Sastry, 2006, GECCO '06.

When Huge Is Routine: Scaling Genetic Algorithms and Estimation of Distribution Algorithms via Data-Intensive Computing

Xavier Llorà, David E. Goldberg, Roy H. Campbell, 2010, Parallel and Distributed Computational Intelligence.

Analysis and Improvement of Fitness Exploitation in XCS: Bounding Models, Tournament Selection, and Bilateral Accuracy

Martin V. Butz, David E. Goldberg, Kurian K. Tharakunnel, 2003, Evolutionary Computation.

Using Previous Models to Bias Structural Learning in the Hierarchical BOA

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2012, Evolutionary Computation.

Scaling eCGA model building via data-intensive computing

Xavier Llorà, David E. Goldberg, Roy H. Campbell, 2010, IEEE Congress on Evolutionary Computation.

Learning Linkage

David E. Goldberg, Georges R. Harik, D. Goldberg, 1996, FOGA.

Performance of evolutionary algorithms on NK landscapes with nearest neighbor interactions and tunable overlap

Martin V. Butz, David E. Goldberg, Martin Pelikan, 2009, GECCO '09.

Dynamic Uniform Scaling for Multiobjective Genetic Algorithms

David E. Goldberg, Gerulf K. M. Pedersen, 2004, GECCO.

Meandre: Semantic-Driven Data-Intensive Flows in the Clouds

Xavier Llorà, David E. Goldberg, Loretta Auvil, 2008, 2008 IEEE Fourth International Conference on eScience.

Genetic and Evolutionary Algorithms in the Real World

David E. Goldberg, D. Goldberg, 1999 .

Scalability of a Hybrid Extended Compact Genetic Algorithm for Ground State Optimization of Clusters

David E. Goldberg, Kumara Sastry, Duane D. Johnson, 2007 .

Creating Scalable Reform in Engineering Education Through Low-Cost In- trinsic Motivation Course Conversions of Engineering Courses

David E. Goldberg, Michael C. Loui, Geoffrey L. Herman, 2013 .

A Fitness Inheritance Evolutionary Algorithm for Solving Bi-criteria Flexible Process Sequencing Problems

David E. Goldberg, Kumara Sastry, Jian-hung Chen, 2007 .

Computational Complexity of the XCS Classifier System

Martin V. Butz, David E. Goldberg, Pier Luca Lanzi, 2005 .

Fitness Inheritance In Multi-objective Optimization

David E. Goldberg, Kumara Sastry, Shinn-Ying Ho, 2002, GECCO.

Schaum's outline of theory and problems of beginning chemistry

David E. Goldberg, 1999 .

The compact classifier system: scalability analysis and first results

Xavier Llorà, David E. Goldberg, Kumara Sastry, 2005, 2005 IEEE Congress on Evolutionary Computation.

Hierarchical Bayesian Optimization Algorithm

David E. Goldberg, Martin Pelikan, D. Goldberg, 2006, Scalable Optimization via Probabilistic Modeling.

Parallel Recombinative Simulated Annealing: A Genetic Algorithm

David E. Goldberg, Samir W. Mahfoud, D. Goldberg, 1995, Parallel Comput..

Substructural Neighborhoods for Local Search in the Bayesian Optimization Algorithm

Martin V. Butz, David E. Goldberg, Martin Pelikan, 2006, PPSN.

A niched Pareto genetic algorithm for multiobjective optimization

David E. Goldberg, Jeffrey Horn, Nicholas Nafpliotis, 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

Conquering hierarchical difficulty by explicit chunking: substructural chromosome compression

David E. Goldberg, Tian-Li Yu, 2006, GECCO '06.

Online population size adjusting using noise and substructural measurements

David E. Goldberg, Kumara Sastry, Tian-Li Yu, 2005, 2005 IEEE Congress on Evolutionary Computation.

Efficient Interactive Weight Tuning For Tts Synthesis: Reducing User Fatigue By Improving User Consistency

Xavier Llorà, David E. Goldberg, Kumara Sastry, 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

SEARCH, Blackbox Optimization, And Sample Complexity

David E. Goldberg, Hillol Kargupta, D. Goldberg, 1996, FOGA.

From Genetic and Evolutionary Optimization to the Design of Conceptual Machines

David E. Goldberg, 1998 .

Fluctuating crosstalk, deterministic noise, and GA scalability

David E. Goldberg, Paul Winward, D. Goldberg, 2006, GECCO.

Improving the Performance of a Pittsburgh Learning Classifier System Using a Default Rule

Martin V. Butz, David E. Goldberg, Jaume Bacardit, 2005, IWLCS.

Genetic algorithms and Machine Learning

David E. Goldberg, John H. Holland, J. Holland, 1988, Machine Learning.

Probability matching, the magnitude of reinforcement, and classifier system bidding

David E. Goldberg, D. Goldberg, 2004, Machine Learning.

Polynomial complexity blackbox search: lessons from the SEARCH framework

David E. Goldberg, Hillol Kargupta, D. Goldberg, 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

Genetic and evolutionary algorithms come of age

David E. Goldberg, D. Goldberg, 1994, CACM.

Tightness Time for the Linkage Learning Genetic Algorithm

David E. Goldberg, Ying-Ping Chen, D. Goldberg, 2003, GECCO.

Genetic Algorithms and Innovation

David E. Goldberg, 2002 .

Key Elements Extraction in Online Collaborative Environments

Xavier Llorà, David E. Goldberg, Hiroshi Tamura, 2007, ICEIS.

SIMPLIFYING MULTIOBJECTIVE OPTIMIZATION USING GENETIC ALGORITHMS

David E. Goldberg, Patrick M. Reed, Barbara S. Minsker, 2003 .

Genetic Algorithms with Sharing for Multimodalfunction Optimization

David E. Goldberg, Jon T. Richardson, D. Goldberg, 1987, ICGA.

Genetic Algorithms and the Variance of Fitness

David E. Goldberg, Mike Rudnick, D. Goldberg, 1991, Complex Syst..

Binary rule encoding schemes: a study using the compact classifier system

Xavier Llorà, David E. Goldberg, Kumara Sastry, 2005, GECCO '05.

First Cognitive Capabilities in the Anticipatory Classifier System

Martin V. Butz, David E. Goldberg, Joachim Hoffmann, 2000 .

Convergence Time for the Linkage Learning Genetic Algorithm

David E. Goldberg, Ying-Ping Chen, D. Goldberg, 2004, Evolutionary Computation.

The mGA1.0: A common LISP implementation of a messy genetic algorithm

David E. Goldberg, Travis Kerzic, 1990 .

Modeling selection pressure in XCS for proportionate and tournament selection

David E. Goldberg, Kumara Sastry, Pier Luca Lanzi, 2007, GECCO '07.

Genetic Algorithms and Walsh Functions: Part II, Deception and Its Analysis

David E. Goldberg, D. Goldberg, 1989, Complex Syst..

Evolvable Modeling: structural adaptation through hierarchical evolution for 3-D model-based vision*

David E. Goldberg, Thomas S. Huang, Thang C. Nguyen, 1993 .

Compact genetic algorithm: A litmus test for genetic algorithm applicability

David E. Goldberg, Eric Michielssen, Daniel S. Weile, 2000 .

Optimizing Global-Local Search Hybrids

David E. Goldberg, Siegfried Vössner, D. Goldberg, 1999, GECCO.

Wise Breeding GA via Machine Learning Techniques for Function Optimization

Xavier Llorà, David E. Goldberg, D. Goldberg, 2003, GECCO.

Binary rule encoding schemes: a study using the compact classifier system

Xavier Llorà, David E. Goldberg, Kumara Sastry, 2005, GECCO '05.

Delineating Topic and Discussant Transitions in Online Collaborative Environments

Xavier Llorà, David E. Goldberg, Hiroshi Tamura, 2007, ICEIS.

Toward routine billion-variable optimization using genetic algorithms

Xavier Llorà, David E. Goldberg, Kumara Sastry, 2007, Complex..

Genetic Algorithm Design Inspired by Organizational Theory: Pilot Study of a Dependency Structure Matrix Driven Genetic Algorithm

David E. Goldberg, Tian-Li Yu, Ali Yassine, 2003, GECCO.

Toward a Better Understanding of Mixing in Genetic Algorithms

Dirk Thierens, David E. Goldberg, Kalyanmoy Deb, 1993 .

A Critical Review of Classifier Systems

David E. Goldberg, Stewart W. Wilson, D. Goldberg, 1989, ICGA.

Are Multiple Runs of Genetic Algorithms Better than One?

David E. Goldberg, Erick Cantú-Paz, D. Goldberg, 2003, GECCO.

FOX-GA: A Genetic Algorithm for Generating and Analyzing Battlefield Courses of Action

David E. Goldberg, C. C. Hayes, J. L. Schlabach, 1999, Evolutionary Computation.

Efficiency Enhancement of Probabilistic Model Building Genetic Algorithms

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2004, ArXiv.

Entrepreneurial Engineer: Ready for the 21st Century

David E. Goldberg, D. Goldberg, 2005 .

Dependency Structure Matrix, Genetic Algorithms, and Effective Recombination

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2009, Evolutionary Computation.

Classifier prediction based on tile coding

Daniele Loiacono, David E. Goldberg, Stewart W. Wilson, 2006, GECCO '06.

The Practitioner's Role in Competent Search and Optimization Using Genetic Algorithms

David E. Goldberg, Patrick M. Reed, Barbara S. Minsker, 2001 .

Evolutionary Algorithm for Large Scale Problems

David E. Goldberg, Kumara Sastry, Alexandre C. B. Delbem, 2007, Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007).

Don't Worry, Be Messy

Kalyanmoy Deb, David E. Goldberg, Bradley Korb, 1991, ICGA.

Toward a Control Map for Niching

David E. Goldberg, Jeffrey Horn, D. Goldberg, 1998, FOGA.

Two analysis tools to describe the operation of classifier systems

David E. Goldberg, Manuel Valenzuela-Rendon, D. Goldberg, 1989 .

Military antenna design using simple and competent genetic algorithms

David E. Goldberg, Scott Santarelli, Tian-Li Yu, 2006, Math. Comput. Model..

The Genetic Algorithm Approach: Why, How, and What Next?

David E. Goldberg, D. Goldberg, 1986 .

Engineering Education Reform in a Large Research University: Strategies and Reflections on Innovation

David E. Goldberg, Brian K. Schertz, Karen K. Hyman, 2010, 2010 IEEE Transforming Engineering Education: Creating Interdisciplinary Skills for Complex Global Environments.

Communication Gap Management for Fertile Community

Xavier Llorà, David E. Goldberg, Naohiro Matsumura, 2007, Soft Comput..

Bayesian Optimization Algorithm, Population Sizing, and Time to Convergence

David E. Goldberg, Martin Pelikan, Erick Cantú-Paz, 2000, GECCO.

Genetic Algorithms, Selection Schemes, and the Varying Effects of Noise

David E. Goldberg, Brad L. Miller, D. Goldberg, 1996, Evolutionary Computation.

Real-Coded Extended Compact Genetic Algorithm Based on Mixtures of Models

David E. Goldberg, Kumara Sastry, Pier Luca Lanzi, 2008, Linkage in Evolutionary Computation.

Combining The Strengths Of Bayesian Optimization Algorithm And Adaptive Evolution Strategies

David E. Goldberg, Martin Pelikan, Shigeyoshi Tsutsui, 2002, GECCO.

A self adaptive hybrid genetic algorithm

David E. Goldberg, Barbara S. Minsker, Felipe P. Espinoza, 2001 .

From Twomax To The Ising Model: Easy And Hard Symmetrical Problems

David E. Goldberg, Bart Naudts, Clarissa Van Hoyweghen, 2002, GECCO.

The Making of A Whole New Engineer: Four Unexpected Lessons for Engineering Educators and Education Researchers

David E. Goldberg, Mark Somerville, D. Goldberg, 2015 .

Implicit Niching in a Learning Classifier System: Nature's Way

David E. Goldberg, Kalyanmoy Deb, Jeffrey Horn, 1994, Evolutionary Computation.

A Genetic Algorithm for Developing Modular Product Architectures

David E. Goldberg, Tian-Li Yu, Ali A. Yassine, 2003 .

Linkage Learning, Rule Representation, and the X-Ary Extended Compact Classifier System

Xavier Llorà, David E. Goldberg, Kumara Sastry, 2008, IWLCS.

Genetic Programming for Multiscale Modeling

David E. Goldberg, Kumara Sastry, Pascal Bellon, 2004 .

Improving the efficiency of the extended compact genetic algorithm

David E. Goldberg, Kumara Sastry, Thyago S. P. C. Duque, 2008, GECCO '08.

Combining Reliability and Pareto Optimality—An Approach Using Stochastic Multi-Objective Genetic Algorithms

David E. Goldberg, Abhishek Singh, Barbara S. Minsker, 2003 .

Combating user fatigue in iGAs: partial ordering, support vector machines, and synthetic fitness

Xavier Llorà, David E. Goldberg, Kumara Sastry, 2005, GECCO '05.

Pruefer Numbers and Genetic Algorithms: A Lesson on How the Low Locality of an Encoding Can Harm the Performance of GAs

Franz Rothlauf, David E. Goldberg, D. Goldberg, 2000, PPSN.

Do not match, inherit: fitness surrogates for genetics-based machine learning techniques

Xavier Llorà, David E. Goldberg, Kumara Sastry, 2007, GECCO '07.

Gradient descent methods in learning classifier systems: improving XCS performance in multistep problems

Martin V. Butz, David E. Goldberg, Pier Luca Lanzi, 2005, IEEE Transactions on Evolutionary Computation.

Optimal sampling in a noisy genetic algorithm for risk-based remediation design

David E. Goldberg, Barbara S. Minsker, Gayathri Gopalakrishnan, 2001 .

Prediction update algorithms for XCSF: RLS, Kalman filter, and gain adaptation

Daniele Loiacono, David E. Goldberg, Stewart W. Wilson, 2006, GECCO '06.

Performance Evaluation and Population Reduction for a Self Adaptive Hybrid Genetic Algorithm (SAHGA)

David E. Goldberg, Barbara S. Minsker, Felipe P. Espinoza, 2003, GECCO.

Automated Global Structure Extraction for Effective Local Building Block Processing in XCS

Martin V. Butz, Xavier Llorà, David E. Goldberg, 2006, Evolutionary Computation.

Genetic Algorithms, Clustering, and the Breaking of Symmetry

David E. Goldberg, Martin Pelikan, D. Goldberg, 2000, PPSN.

Empirical analysis of generalization and learning in XCS with gradient descent

Martin V. Butz, David E. Goldberg, Pier Luca Lanzi, 2007, GECCO '07.

Bayesian Optimization Algorithm: From Single Level to Hierarchy

David E. Goldberg, Martin Pelikan, D. Goldberg, 2002 .

Communication Gaps in Social Networks

Xavier Llorà, David E. Goldberg, Naohiro Matsumura, 2005, WSTST.

On becoming a reflective practitioner

David E. Goldberg, D. Goldberg, 2018, GECCO.

Scaling Genetic Algorithms Using MapReduce

Xavier Llorà, David E. Goldberg, Roy H. Campbell, 2009, 2009 Ninth International Conference on Intelligent Systems Design and Applications.

A new approach for multi-label classification based on default hierarchies and organizational learning

Xavier Llorà, David E. Goldberg, André Carlos Ponce de Leon Ferreira de Carvalho, 2008, GECCO '08.

The Nonuniform Walsh-Schema Transform

David E. Goldberg, Clayton L. Bridges, D. Goldberg, 1990, FOGA.

The compact genetic algorithm

David E. Goldberg, Fernando G. Lobo, Georges R. Harik, 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

Evaluation Consistency in iGAs: User Contradictions as Cycles in Partial-Ordering Graphs

David E. Goldberg, Kumara Sastry, Xavier Llorà, 2005 .

Sizing Populations for Serial and Parallel Genetic Algorithms

David E. Goldberg, D. Goldberg, 1989, ICGA.

Money, Work, and You

David E. Goldberg, D. Goldberg, 2005 .

Optimal Sampling For Genetic Algorithms

David E. Goldberg, Brad L. Miller, D. Goldberg, 1996 .

Students As The Key To Unleashing Student Engagement: The Theory, Design, & Launch Of A Scalable, Student Run Learning Community At Xx

David E. Goldberg, Russell Korte, D. Goldberg, 2010 .

Designing a new elitist Nondominated Sorted Genetic Algorithm for a multiobjective long term groundwater monitoring application

David E. Goldberg, Patrick M. Reed, Barbara S. Minsker, 2001 .

Redundant Representations in Evolutionary Computation

Franz Rothlauf, David E. Goldberg, D. Goldberg, 2003, Evolutionary Computation.

Bayesian optimization algorithm, decision graphs, and Occam's razor

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2001 .

A Genetic Algorithm for Parallel Simulated Annealing

David E. Goldberg, Samir W. Mahfoud, D. Goldberg, 1992, PPSN.

Genetic Algorithms, Tournament Selection, and the Effects of Noise

David E. Goldberg, Brad L. Miller, D. Goldberg, 1995, Complex Syst..

The Design of Innovation: Lessons from and for Competent Genetic Algorithms

David E. Goldberg, D. Goldberg, 2002 .

MGA in C: A Messy Genetic Algorithm in C

David E. Goldberg, Kalyanmoy Deb, D. Goldberg, 1991 .

Three Tools of Conceptual Engineering

David E. Goldberg, 2002 .

Construction of high-order deceptive functions using low-order Walsh coefficients

David E. Goldberg, D. Goldberg, 1992, Annals of Mathematics and Artificial Intelligence.

Decision making in a hybrid genetic algorithm

David E. Goldberg, Fernando G. Lobo, D. Goldberg, 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

Sub-structural niching in estimation of distribution algorithms

Hussein A. Abbass, David E. Goldberg, Kumara Sastry, 2005, GECCO '05.

Bounding the Population Size in XCS to Ensure Reproductive Opportunities

Martin V. Butz, David E. Goldberg, D. Goldberg, 2003, GECCO.

Tackling multimodal problems in hybrid genetic algorithms

David E. Goldberg, Scott A. Burns, Prasanna V. Parthasarathy, 2001 .

Dependency Structure Matrix Analysis: Offline Utility of the Dependency Structure Matrix Genetic Algorithm

David E. Goldberg, Tian-Li Yu, D. Goldberg, 2004, GECCO.

Speeding-Up Pittsburgh Learning Classifier Systems: Modeling Time and Accuracy

Martin V. Butz, Xavier Llorà, David E. Goldberg, 2004, PPSN.

A Simple Real-Coded Extended Compact Genetic Algorithm

David E. Goldberg, Kumara Sastry, Pier Luca Lanzi, 2007, 2007 IEEE Congress on Evolutionary Computation.

Substructrual surrogates for learning decomposable classification problems: implementation and first results

David E. Goldberg, Kumara Sastry, Ester Bernadó-Mansilla, 2007, GECCO '07.

An Investigation of Niche and Species Formation in Genetic Function Optimization

Kalyanmoy Deb, David E. Goldberg, D. Goldberg, 1989, ICGA.

Takeover Time in a Noisy Environment

David E. Goldberg, Yuji Sakamoto, D. Goldberg, 1997, ICGA.

Enhancing Command Communications and Innovation with SAINT:Semantics, Adaptation, and Influence in Networked Teams

David E. Goldberg, Xavier Llora, 2009 .

Diploidy and Dominance in Artificial Genetic Search

David E. Goldberg, Robert E. Smith, D. Goldberg, 1992, Complex Syst..

Effect of Pure Error-Based Fitness in XCS

Martin V. Butz, David E. Goldberg, Pier Luca Lanzi, 2005, IWLCS.

INNOVATION AND CREATIVITY SUPPORT VIA CHANCE DISCOVERY, GENETIC ALGORITHMS, AND DATA MINING

Xavier Llorà, David E. Goldberg, Loretta Auvil, 2006 .

Large-Scale Permutation Optimization with the Ordering Messy Genetic Algorithm

David E. Goldberg, Dimitri Knjazew, D. Goldberg, 2000, PPSN.

Model accuracy in the Bayesian optimization algorithm

David E. Goldberg, Martin Pelikan, Cláudio F. Lima, 2011, Soft Comput..

3 Lessons of Genetic Algorithms for Computational Innovation

David E. Goldberg, D. Goldberg, 1999 .

Multi-objective bayesian optimization algorithm

David E. Goldberg, Martin Pelikan, Nazan Khan, 2002 .

Genetic Algorithms and Rules Learning in Dynamic System Control

David E. Goldberg, D. Goldberg, 1985, ICGA.

Simplex crossover and linkage identification: single-stage evolution vs. multi-stage evolution

David E. Goldberg, Shigeyoshi Tsutsui, D. Goldberg, 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

Genetic Algorithms: A Bibliography

David E. Goldberg, Kelsey Milman, D. Goldberg, 1997 .

Multimodal Deceptive Functions

Kalyanmoy Deb, David E. Goldberg, Jeffrey Horn, 1993, Complex Syst..

Using Previous Models to Bias Structural Learning in the Hierarchical BOA

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2008, Evolutionary Computation.

Multiobjective Estimation of Distribution Algorithms

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2006, Scalable Optimization via Probabilistic Modeling.

Evaluation relaxation using substructural information and linear estimation

David E. Goldberg, Kumara Sastry, Cláudio F. Lima, 2006, GECCO '06.

Investigating Generalization in the Anticipatory Classifier System

Martin V. Butz, David E. Goldberg, Wolfgang Stolzmann, 2000, PPSN.

Parallel Genetic Algorithms with Distributed Panmictic Populations

David E. Goldberg, 1999 .

Creating Low-cost Intrinsic Motivation Course Conversions in a Large Required Engineering Course

David E. Goldberg, Geoffrey L. Herman, Mark Somerville, 2012 .

Messy Genetic Algorithms: Motivation, Analysis, and First Results

Kalyanmoy Deb, David E. Goldberg, Bradley Korb, 1989, Complex Syst..

Designing a competent simple genetic algorithm for search and optimization

David E. Goldberg, Patrick M. Reed, Barbara S. Minsker, 2000 .

Extending XCSF beyond linear approximation

Daniele Loiacono, David E. Goldberg, Stewart W. Wilson, 2005, GECCO '05.

Bad Codings and the Utility of Well-Designed Genetic Algorithms

Franz Rothlauf, David E. Goldberg, Armin Heinzl, 2000, GECCO.

Massive Multimodality, Deception, and Genetic Algorithms

Kalyanmoy Deb, David E. Goldberg, Jeffrey Horn, 1992, PPSN.

Probability Matching, the Magnitude of Reinforcement, and Classifier System Bidding

David E. Goldberg, D. Goldberg, 1990, Machine Learning.

From Theory to Air Force Practice: Applications and Non-Binary Extensions of Probabilistic Model-Building Genetic Algorithms

David E. Goldberg, 2006 .

Quality-time analysis of multi-objective evolutionary algorithms

David E. Goldberg, Shinn-Ying Ho, Jian-Hung Chen, 2005, GECCO '05.

Life Skills and Leadership for Engineers

David E. Goldberg, 1994 .

Designing Competent Mutation Operators Via Probabilistic Model Building of Neighborhoods

David E. Goldberg, Kumara Sastry, D. Goldberg, 2004, GECCO.

The compact classifier system: motivation, analysis, and first results

Xavier Llorà, David E. Goldberg, Kumara Sastry, 2005, GECCO '05.

XCS with computed prediction in multistep environments

Daniele Loiacono, David E. Goldberg, Stewart W. Wilson, 2005, GECCO '05.

The Design of Innovation

David E. Goldberg, D. Goldberg, 2002, Genetic Algorithms and Evolutionary Computation.

Chances and Marketing: On-line Conversation Analysis for Creative Scenario Discussion

David E. Goldberg, Yukio Ohsawa, Hiroshi Tamura, 2004 .

SIGNAL TIMING DETERMINATION USING GENETIC ALGORITHMS

David E. Goldberg, Rahim F Benekohal, Mark D Foy, 1992 .

Toward an Understanding of the Quality and Efficiency of Model Building for Genetic Algorithms

David E. Goldberg, Tian-Li Yu, 2004, GECCO.

Modified Linkage Learning Genetic Algorithm For Difficult Non-stationary Problems

David E. Goldberg, Abhishek Singh, Ying-Ping Chen, 2002, GECCO.

The - ary extended compact classifier system: Linkage learning in Pittsburgh LCS

David E. Goldberg, Kumara Sastry, Luis de la Ossa, 2007 .

Present, Don't Speak

David E. Goldberg, D. Goldberg, 2005 .

Hierarchical BOA Solves Ising Spin Glasses and MAXSAT

David E. Goldberg, Martin Pelikan, D. Goldberg, 2003, GECCO.

3 Lessons I Learned from John H. Holland

David E. Goldberg, 2016, SEVO.

Gradient-Based Learning Updates Improve XCS Performance in Multistep Problems

Martin V. Butz, David E. Goldberg, Pier Luca Lanzi, 2004, GECCO.

Application of evolutionary algorithms and neural network concepts to the design of low-cost, wideband antenna arrays

David E. Goldberg, Scott Santarelli, Tian-Li Yu, 2007, SPIE Defense + Commercial Sensing.

Bounding the Effect of Noise in Multiobjective Learning Classifier Systems

Xavier Llorà, David E. Goldberg, D. Goldberg, 2003, Evolutionary Computation.

Search space boundary extension method in real-coded genetic algorithms

David E. Goldberg, Shigeyoshi Tsutsui, D. Goldberg, 2001, Inf. Sci..

Variable Default Hierarchy Separation in a Classifier System

David E. Goldberg, Robert E. Smith, D. Goldberg, 1990, FOGA.

Ensuring Building Block Supply

David E. Goldberg, 2002 .

The Theory of Virtual Alphabets

David E. Goldberg, D. Goldberg, 1990, PPSN.

An information theoretic method for developing modular architectures using genetic algorithms

David E. Goldberg, Tian-Li Yu, Ali A. Yassine, 2007 .

Genetic Algorithms and Walsh Functions: Part I, A Gentle Introduction

David E. Goldberg, D. Goldberg, 1989, Complex Syst..

ENGINEERING OPTIMIZATION VIA GENETIC ALGORITHM, IN WILL

David E. Goldberg, Manohar P. Samtani, D. Goldberg, 1986 .

Introducing a Genetic Generalization Pressure to the Anticipatory Classifier System - Part 1: Theoretical approach

Martin V. Butz, David E. Goldberg, Wolfgang Stolzmann, 2000, GECCO.

Speeding online synthesis via enforced selecto-recombination

Xavier Llorà, David E. Goldberg, Kumara Sastry, 2008, GECCO '08.

Resource management and scalability of the XCSF learning classifier system

Martin V. Butz, Xavier Llorà, David E. Goldberg, 2012, Theor. Comput. Sci..

Military Antenna Design Using a Simple Genetic Algorithm and hBOA

David E. Goldberg, Scott Santarelli, Tian-Li Yu, 2006, Scalable Optimization via Probabilistic Modeling.

The importance of pairwork in interdisciplinary and educational initiatives

David E. Goldberg, D. Goldberg, 2009, 2009 39th IEEE Frontiers in Education Conference.

The intrinsic-motivation course design method

David E. Goldberg, Jonathan Stolk, Geoffrey L. Herman, 2017 .

Generalization in the XCSF Classifier System: Analysis, Improvement, and Extension

Daniele Loiacono, David E. Goldberg, Stewart W. Wilson, 2007, Evolutionary Computation.

Real-coded ECGA for solving decomposable real-valued optimization problems

David E. Goldberg, Kumara Sastry, Minqiang Li, 2007, 2007 IEEE Congress on Evolutionary Computation.

RapidAccurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms

Kalyanmoy Deb, David E. Goldberg, Hillol Kargupta, 1993, ICGA.

Using Time Efficiently: Genetic-Evolutionary Algorithms and the Continuation Problem

David E. Goldberg, 1999, GECCO.

Tournament Selection: Stable Fitness Pressure in XCS

Martin V. Butz, David E. Goldberg, Kumara Sastry, 2003, GECCO.

Discovering Building Blocks for Human Based Genetic Algorithms

David E. Goldberg, Kumara Sastry, Xavier Llora, 2007 .

Zen and the Art of Genetic Algorithms

David E. Goldberg, D. Goldberg, 1989, ICGA.

Enhancing the Efficiency of the ECGA

David E. Goldberg, Kumara Sastry, Thyago S. P. C. Duque, 2008, PPSN.

The multi-label OCS with a genetic algorithm for rule discovery: implementation and first results

David E. Goldberg, André Carlos Ponce de Leon Ferreira de Carvalho, Thyago S. P. C. Duque, 2009, GECCO '09.

Toward routine billion-variable optimization using genetic algorithms: Short Communication

Xavier Llorà, David E. Goldberg, Kumara Sastry, 2007 .

Efficiency Enhancement of Estimation of Distribution Algorithms

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2006, Scalable Optimization via Probabilistic Modeling.

Quick Stroking: A Fast and Accurate Algorithm for Time-Optimal Valve Closure Synthesis

David E. Goldberg, 1985 .

Linkage learning, overlapping building blocks, and systematic strategy for scalable recombination

David E. Goldberg, Kumara Sastry, Tian-Li Yu, 2005, GECCO '05.

Sporadic model building for efficiency enhancement of hierarchical BOA

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2006, GECCO.

Sufficient conditions for deceptive and easy binary functions

Kalyanmoy Deb, David E. Goldberg, D. Goldberg, 1994, Annals of Mathematics and Artificial Intelligence.

Network Random KeysA Tree Representation Scheme for Genetic and Evolutionary Algorithms

Franz Rothlauf, David E. Goldberg, Armin Heinzl, 2002, Evolutionary Computation.

Gradient Descent Methods in Learning Classifier Systems

Martin V. Butz, David E. Goldberg, Pier Luca Lanzi, 2004 .

Control system optimization using genetic algorithms

David E. Goldberg, K. Krishnakumar, D. Goldberg, 1992 .

Population Sizing to Go: Online Adaptation Using Noise and Substructural Measurements

David E. Goldberg, Kumara Sastry, Tian-Li Yu, 2007, Parameter Setting in Evolutionary Algorithms.

Ordering Genetic Algorithms and Deception

Kalyanmoy Deb, David E. Goldberg, Hillol Kargupta, 1992, PPSN.

Time Complexity of genetic algorithms on exponentially scaled problems

David E. Goldberg, Martin Pelikan, Fernando G. Lobo, 2000, GECCO.

Evolutionary Computation As A Form Of Organization

David E. Goldberg, Alexander Kosorukoff, D. Goldberg, 2002, GECCO.

Schaum's Outline of Theory and Problems of Programming with Assembly Language

David E. Goldberg, Jacqueline A. Jones, Pat H. Sterbenz, 1988 .

Genetic Algorithms in Search Optimization and Machine Learning

David E. Goldberg, D. Goldberg, 1988 .

Efficient Discretization Scheduling In Multiple Dimensions

David E. Goldberg, Laura A. Albert, 2002, GECCO.

The Six Minds of a Whole New Engineer

David E. Goldberg, 2015 .

Let's get ready to rumble redux: crossover versus mutation head to head on exponentially scaled problems

David E. Goldberg, Kumara Sastry, D. Goldberg, 2007, GECCO '07.

A new method for linkage learning in the ECGA

David E. Goldberg, Thyago S. P. C. Duque, 2009, GECCO '09.

Ensuring Building Block Growth

David E. Goldberg, 2002 .

The Everyday Engineering of Organizational and Engineering Innovation

David E. Goldberg, D. Goldberg, 2004 .

Genetic Algorithms, Efficiency Enhancement, And Deciding Well With Differing Fitness Bias Values

David E. Goldberg, Kumara Sastry, 2002, GECCO.

Dynamic System Control Using Rule Learning and Genetic Algorithms

David E. Goldberg, D. Goldberg, 1985, IJCAI.

Towards billion-bit optimization via a parallel estimation of distribution algorithm

Xavier Llorà, David E. Goldberg, Kumara Sastry, 2007, GECCO '07.

Sub-structural Niching in Non-stationary Environments

Hussein A. Abbass, David E. Goldberg, Kumara Sastry, 2004, Australian Conference on Artificial Intelligence.

Hierarchical Problem Solving and the Bayesian Optimization Algorithm

David E. Goldberg, Martin Pelikan, D. Goldberg, 2000, GECCO.

Binary Representation in Gene Expression Programming: Towards a Better Scalability

Jose Garcia Moreno-Torres, David E. Goldberg, Xavier Llorà, 2009, ISDA.

Little Models, Big Results

David E. Goldberg, 2005, Australian Conference on Artificial Intelligence.

Analyzing Trends in the Blogosphere Using Human-Centered Analysis and Visualization Tools

Xavier Llorà, David E. Goldberg, Noriko Imafuji Yasui, 2007, ICWSM.

BUILDING-BLOCK SUPPLY IN GENETIC PROGRAMMING

David E. Goldberg, David J. Hill, Kumara Sastry, 2003 .

Introducing Subchromosome Representations to the Linkage Learning Genetic Algorithm

David E. Goldberg, Ying-Ping Chen, D. Goldberg, 2004, GECCO.

Genetic Algorithm-Based Searching Method for Piping Path Routing in Coal-Fired Boiler Buildings

David E. Goldberg, Naohiro Kusumi, Noriyuki Ichinose, 2011 .

Oiling the Wheels of Change: The Role of Adaptive Automatic Problem Decomposition in Non-Stationary Environments pdf

Hussein A. Abbass, David E. Goldberg, Kumara Sastry, 2005, ArXiv.

Multiple-Deme Parallel Estimation of Distribution Algorithms: Basic Framework and Application

David E. Goldberg, Chang Wook Ahn, R. S. Ramakrishna, 2003, PPAM.

Modeling XCS in class imbalances: population size and parameter settings

David E. Goldberg, Kumara Sastry, Ester Bernadó-Mansilla, 2007, GECCO '07.

Multiobjective hBOA, clustering, and scalability

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2005, GECCO '05.

Real-coded Bayesian Optimization Algorithm

David E. Goldberg, Chang Wook Ahn, R. S. Ramakrishna, 2006, Towards a New Evolutionary Computation.

Genetic algorithm design of Pareto optimal broadband microwave absorbers

David E. Goldberg, Eric Michielssen, Daniel S. Weile, 1996 .

Let's Get Ready to Rumble: Crossover Versus Mutation Head to Head

David E. Goldberg, Kumara Sastry, D. Goldberg, 2004, GECCO.

Towards Building Block Propagation in XCS: A Negative Result and Its Implications

Martin V. Butz, David E. Goldberg, Kurian K. Tharakunnel, 2003, GECCO.

Providing Collaborative Education with an International Dimension: An Ulster University and Pennsylvania State University Case Study

David E. Goldberg, Robert Eadie, David Comiskey, 2015, Int. J. 3 D Inf. Model..

Philosophy and Engineering: Reflections on Practice, Principles and Process

David E. Goldberg, Diane P. Michelfelder, Natasha McCarthy, 2016, IEEE Transactions on Education.

On the Scalability of Parallel Genetic Algorithms

David E. Goldberg, Erick Cantú-Paz, D. Goldberg, 1999, Evolutionary Computation.

Performance Analyses of Factorization Based on Gaussian PDF In rECGA

David E. Goldberg, Kumara Sastry, Minqiang Li, 2007, Third International Conference on Natural Computation (ICNC 2007).

Facetwise Analysis of XCS for Problems With Class Imbalances

David E. Goldberg, Kumara Sastry, Pier Luca Lanzi, 2009, IEEE Transactions on Evolutionary Computation.

Linkage Learning Accuracy in the Bayesian Optimization Algorithm

David E. Goldberg, Martin Pelikan, Kumara Sastry, 2008, Linkage in Evolutionary Computation.

Effective and Reliable Online Classification Combining XCS with EDA Mechanisms

Martin V. Butz, Xavier Llorà, David E. Goldberg, 2006, Scalable Optimization via Probabilistic Modeling.

A hierarchy machine: Learning to optimize from nature and humans

David E. Goldberg, Martin Pelikan, D. Goldberg, 2003, Complex..

Quick Stroking: Design of Time‐optimal Valve Motions

David E. Goldberg, Charles L. Karr, C. L. Karr, 1987 .

Where Does the Good Stuff Go, and Why? How Contextual Semantics Influences Program Structure in Simple Genetic Programming

David E. Goldberg, Una-May O'Reilly, D. Goldberg, 1998, EuroGP.

Adaptive Hybrid Genetic Algorithm for Groundwater Remediation Design

David E. Goldberg, Barbara S. Minsker, Felipe P. Espinoza, 2005 .

Long Path Problems

Kalyanmoy Deb, David E. Goldberg, Jeffrey Horn, 1994, PPSN.

Incorporating User Feedback into Name Disambiguation of Scientific Cooperation Network

Koichi Furukawa, David E. Goldberg, Jim Gray, 2011 .

Linkage Problem , Distribution Estimation , and Bayesian

David E. Goldberg, Erick Cant, NetworksMartin Pelikan, 1998 .

Genetic algorithms and the vVariance of fitness

David E. Goldberg, Mike Rudnick, 2017 .

Philosophy and engineering : an emerging agenda

David E. Goldberg, Ibo van de Poel, D. Goldberg, 2010 .

Design of microvascular flow networks using multi-objective genetic algorithms

David E. Goldberg, Philippe H. Geubelle, Scott R. White, 2008 .

A Multiscale Island Injection Genetic Algorithm for Optimal Groundwater Remediation Design

David E. Goldberg, Meghna Babbar, Barbara Minsker, 2002 .

Mining Social Networks in Message Boards

David E. Goldberg, Naohiro Matsumura, Xavier Llor, 2005 .

Solving Sequence Problems by Building and Sampling Edge Histograms

David E. Goldberg, Martin Pelikan, Shigeyoshi Tsutsui, 2002 .

Change in Engineering Education: One Myth, Two Scenarios, and Three Foci

David E. Goldberg, D. Goldberg, 1996 .

Introducing a Genetic Generalization Pressure to the Anticipatory Classiier System Part 2: Performance Analysis Introducing a Genetic Generalization Pressure to the Anticipatory Classiier System Part 2: Performance Analysis

David E. Goldberg, Wolfgang Stolzmann, D. Goldberg, 2007 .

Genetic programming for multitimescale modeling

David E. Goldberg, Kumara Sastry, Pascal Bellon, 2005 .

Simplex crossover and linkage learning in real-coded GAs

David E. Goldberg, Kumara Sastry, Shigeyoshi Tsutsui, 2001 .

Engineering rigor and its discontents: Philosophical reflection as curative to math-physics envy.

David E. Goldberg, 2009 .

Toward a Mechanics of Conceptual Machines

David E. Goldberg, D. Goldberg, 1995 .

Discovering Chance Scenarios using Small-World KeyGraphs and Evolutionary Computation

David E. Goldberg, Yukio Ohsawa, Kei Ohnishi, 2004 .

An overview of the parameter-less genetic algorithm

David E. Goldberg, Fernando G. Lobo, D. Goldberg, 2022 .

Fostering motivation as a class objective in a large engineering class for second-year students: a narrative approach

David E. Goldberg, Geoffrey L. Herman, Kathryn F. Trenshaw, 2014 .

The Entrepreneurial Engineer

David E. Goldberg, D. Goldberg, 2006 .

Node Histogram vs . Edge Histogram : A Comparison of PMBGAs in Permutation Domains

David E. Goldberg, Martin Pelikan, Shigeyoshi Tsutsui, 2006 .

Optimization of Semiempirical Quantum Chemistry Methods via Multiobjective Genetic Algorithms: Accurate Photodynamics for Larger Molecules and Longer Time Scales

David E. Goldberg, Kumara Sastry, A. L. Thompson, 2007 .

Designing Efficient Genetic and Evolutionary Algorithm Hybrids

David E. Goldberg, D. Goldberg, Ying-Ping Chen, 2005 .

The Existential Pleasures of Genetic Algorithms the Existential Pleasures of Genetic Algorithms

David E. Goldberg, Samuel Florman, D. Goldberg, 1994 .