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Continuous endpoint data mining with ExSTraCS: a supervised learning classifier system.
Ryan Urbanowicz, Nirajan Ramanand, and Jason Moore
Proceedings of the 17th annual conference companion on Genetic and evolutionary computation. ACM Press. 2015.
Retooling fitness for noisy problems in a supervised Michigan-style learning classifier system.
Ryan Urbanowicz, and Jason Moore
Proceedings of the 17th annual conference companion on Genetic and evolutionary computation. ACM Press. 2015.
ExSTraCS 2.0: Addressing Scalability with a Rule Specificity Limit in a Michigan-Style Supervised Learning Classifier System for Classification, Prediction, and Knowledge Discovery.
Ryan Urbanowicz and Jason Moore
Evolutionary Intelligence. 8.2-3, 89-116. 2015
ExSTraCS: Rule Based Machine Learning, Classification, and Knowledge Discovery for Complex Problems.
Ryan Urbanowicz
SIGEVOlution Newsletter of the ACM Special Interest Group on Genetic and Evolutionary Computation. 7(2-3). pp. 3-11, 2014
Journal Publications
2015
ExSTraCS 2.0: Addressing Scalability with a Rule Specificity Limit in a Michigan-Style Supervised Learning Classifier System for Classification, Prediction, and Knowledge Discovery.
Ryan Urbanowicz and Jason Moore
Evolutionary Intelligence. 8.2-3, 89-116. 2015
2014
A Classification and Characterization of Two-Locus Pure, Strict Epistatic Models for Simulation and Detection.
Ryan Urbanowicz, Ambrose Granizo-Mackenzie, Jeff Kiralis, and Jason Moore
BioData Mining. 7(1), 8. 2014
2013
A Multi-Core Parallelization Strategy for Statistical Significance Testing in Learning Classifier Systems
James Rudd, Jason Moore, and Ryan Urbanowicz
Journal of Evolutionary Intelligence. 6(2), pp. 127-134. 2013
The Role of Genetic Heterogeneity and Epistasis in Bladder Cancer Susceptibility and Outcome: A Learning Classifier System Approach
Ryan Urbanowicz, Angeline Andrew, Margaret Karagas, and Jason Moore
Journal of the American Medical Informatics Association. BMJ Publishing Group Ltd. 2013.
2012
Predicting Difficulty in Simulated Genetic Models: Metrics for Model Architecture Selection
Ryan Urbanowicz, Jeff Kiralis, Jonathan Fisher, and Jason Moore
BioData Mining. BioMed Central Ltd pp. 15, 2012.
GAMETES: A Fast, Direct Algorithm for Generating Pure, Strict, Epistatic Models with Random Architectures
Ryan Urbanowicz, Jeff Kiralis, Jonathan Fisher, Nicholas Sinnott-Armstrong, Tamra Heberling, and Jason Moore
BioData Mining. BioMed Central Ltd pp. 16, 2012.
An Analysis Pipeline with Statistical and Visualization-Guided Knowledge Discovery for Michigan-Style Learning Classifier Systems
Ryan Urbanowicz, Ambrose Granizo-Mackenzie, and Jason Moore
Computational Intelligence Magazine, pp. 35-45, 2012.
2009
Learning Classifier Systems: A Complete Introduction, Review, and Roadmap
Ryan Urbanowicz and Jason Moore
Journal of Artificial Evolution and Applications. Hindawi Publishing Corporation, 2009.
Conference and Workshop Publications (Peer Reviewed)
2015
Continuous endpoint data mining with ExSTraCS: a supervised learning classifier system.
Ryan Urbanowicz, Nirajan Ramanand, and Jason Moore
Proceedings of the 17th annual conference companion on Genetic and evolutionary computation. ACM Press. 2015.
Retooling fitness for noisy problems in a supervised Michigan-style learning classifier system.
Ryan Urbanowicz, and Jason Moore
Proceedings of the 17th annual conference companion on Genetic and evolutionary computation. ACM Press. 2015.
2014
An Extended Michigan-Style Learning Classifier System for Flexible Supervised Learning, Classification, and Data Mining.
Ryan Urbanowicz, Gediminas Bertasius, and Jason Moore
Parallel Problem Solving in Nature (PPSN XIII). Springer International Publishing. pp. 221-221. 2014.
2013
Rapid Rule Compaction Strategies for Global Knowledge Discovery in a Supervised Learning Classifier System
Jie Tan, Jason Moore and Ryan Urbanowicz
Advances in Artificial Life, ECAL. 12. pp. 110-117. 2013.
A Simple Multi-Core Parallelization Strategy for Learning Classifier System Evaluations
James Rudd, Jason Moore, and Ryan Urbanowicz
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation. ACM Press. 2013.
2012
An Expert Knowledge Guided Michigan-Style Learning Classifier System for the Detection and Modeling of Epistasis and Genetic Heterogeneity
Ryan Urbanowicz, Delany Granizo-Mackenzie, and Jason Moore
Proceedings of the Parallel Problem Solving From Nature - PPSN XII. Springer. pp. 266-275, 2012.
Instance-Linked Attribute Tracking and Feedback for Michigan-Style Supervised Learning Classifier Systems
Ryan Urbanowicz, Ambrose Granizo-Mackenzie, and Jason Moore
Proceedings of the 14th annual conference companion on genetic and evolutionary computation. ACM Press. pp. 927-934, 2012.
2011
Random Artificial Incorporation of Noise in a Learning Classifier System Environment
Ryan Urbanowicz, Nicholas Sinnott-Armstrong, and Jason Moore
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation. ACM Press. pp. 404-413, 2011.
The Application of Pittsburgh-Style Learning Classifier Systems to Address Genetic Heterogeneity and Epistasis in Association Studies
Ryan Urbanowicz and Jason Moore
Proceedings of the Parallel Problem Solving From Nature Conference. Springer pp. 404-413, 2011.
2010
The Application of Michigan-Style Learning Classifier Systems to Address Genetic Heterogeneity and Epistasis in Association Studies
Ryan Urbanowicz and Jason Moore
Proceedings of the 12th annual conference companion on genetic and evolutionary computation. ACM Press. pp. 195-202, 2010.
2008
Mask Functions for the Symbolic Modeling of Epistasis Using Genetic Programming
Ryan Urbanowicz, Bill White, Nate Barney, Jason Moore
Proceedings of the 10th annual conference companion on genetic and evolutionary computation. ACM Press. pp. 339-346, 2008.
Book Chapters (Peer Reviewed)
2013
The Rise of Genetics-Based Machine Learning in Biomedical Data Mining
Ryan Urbanowicz and Jason Moore
Book Chapter for “Methods in Biomedical Informatics: A Pragmatic Approach” Indra Neil Sarkar. Academic Press. pp. 265-311, 2013.
Non-Refereed Publications
2014
ExSTraCS: Rule Based Machine Learning, Classification, and Knowledge Discovery for Complex Problems.
Ryan Urbanowicz
SIGEVOlution Newsletter of the ACM Special Interest Group on Genetic and Evolutionary Computation. 7(2-3). pp. 3-11, 2014
ExSTraCS 2.0 User's Guide
Ryan Urbanowicz and Jason Moore
Included with ExSTraCS 2.0 software download on sourceforge.net.
ExSTraCS 1.0 User's Guide
Ryan Urbanowicz and Jason Moore
Included with ExSTraCS 1.0 software download on sourceforge.net.
2013
Preface: Special Issue on Advances in Learning Classifier Systems
Kamran Shafi, Ryan Urbanowicz, and Muhammad Iqbal
Evolutionary Intelligence, pp. 1-2 2013.
2012
Preface: Special Issue on Advances in Learning Classifier Systems
Danielle Loiacono, Albert Orriols-Puig, and Ryan Urbanowicz
Evolutionary Intelligence, pp. 1-2 2012.
GAMETES User's Guide
Ryan Urbanowicz, Jeff Kiralis, Jonathan Fisher, and Jason Moore
Included with GAMETES software download on sourceforge.net.
Thesis
2012 (PhD)
The Detection and Characterization of Epistasis and Heterogeneity: A Learning Classifier System Approach
Ryan Urbanowicz
Genetics PhD Thesis, Dartmouth College. 2012.
2005 (Masters)
Reassessment of a Ganglioside-Liposome Biosensor
Ryan Urbanowicz
Master’s thesis, Cornell University. 2005.
Abstracts Presented at International Conferences (Peer Reviewed)
2012
A Flexible Learning Classifier System for Classification and Data Mining in Genetic Epidemiology
Ryan Urbanowicz and Jason Moore
International Genetic Epidemiology Society. Oct. 18-20, 2012. Stevenson, WA.
2011
Geneitic Heterogeneity Detection Using a Learning Classifier System
Ryan Urbanowicz, Jeff Kiralis, Jonathan Fisher, Nicholas Sinnott-Armstrong, Tamra Heberling, and Jason Moore
American Society of Human Genetics Conference. October 11-15, 2011. Montreal, Canada.
A Fast, Direct Algorithm for Generating Pure, Strict, Epistatic Models with Random Architectures
Ryan Urbanowicz, Jeff Kiralis, Jonathan Fisher, Nicholas Sinnott-Armstrong, Tamra Heberling, and Jason Moore
American Society of Human Genetics Conference. October 11-15, 2011. Montreal, Canada.
2010
Modeling Disease in the Presence of Genetic Heterogeneity and Epistasis: A Learning Classifier System Approach
Ryan Urbanowicz and Jason Moore
Pacific Symposium on Biocomputing. January 4-8, 2010. Big Island, HI.
2009
A Learning Classifier System Approach to Detecting and Modeling Genetic Heterogeneity in the Presence of Epistasis
Ryan Urbanowicz, and Jason Moore
Genetic and Evolutionary Computing Conference. July 8-12, 2009. Montreal, Canada.
2008
Genetics of Cognitive Decline Post Cancer Chemotherapy: DNA Repair Genes
Tim Ahles, Andrew Saykin, Brenna McDonald, Harker Rhodes, Jason Moore, Ryan Urbanowicz, Gregory Tsongalis, and Tor Tosteson
National Cancer Institute Translational Science Meeting. November 7-9, 2008. Washington, D.C.
Data-Driven Constructive Induction MDR for Genetic Heterogeneity
Ryan Urbanowicz, Delany Granizo-MacKenzie, and Jason Moore
American Society of Human Genetics Annual Meeting. November 11-15, 2008. Philadelphia, PA.
2007
Mask Functions for the Symbolic Modeling of Epistasis
Ryan Urbanowicz, Bill White, Nate Barney and Jason Moore
Pacific Symposium on Biocomputing. January 3-7, 2007. Maui, HI.
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