Dan Ashlock's Vita

Contact Information:
Professor of Mathematics
521 MacNaughton Building
Department of Mathematics and Statistics
University of Guelph, 50 Stone Road East
Guelph, Ontario, Canada N1G 2W1
VOX: 519-824-8166 x 53453
FAX: 519-837-0221 dashlock@uoguelph.ca

Education
B.S., University of Kansas, 1984, Mathematics, with Honors,
B.S., University of Kansas, 1984, Computer Science, with Honors and Distinction,
Ph.D., California Institute of Technology, 1990, Mathematics.

Professional Experience
University of Guelph, Professor of Mathematics 2007-
University of Guelph, Associate Professor of Mathematics 2004-2007
Iowa State University, Associate Professor of Mathematics 1996-2004
Iowa State University, Assistant Professor of Mathematics 1990-1996
California Institute of Technology, Graduate Teaching Assistant 1985-1990
University of Kansas, Undergraduate Teaching Assistant 1979-1985
SoftCole Educational Software, Software Developer, 1981-1984

Research Interests (E-prints)
Bioinformatics and computational biology
Evolutionary computation
Modeling of biological systems
Mathematics Education
Graph theory and combinatorics
Management of Large Data Sets

Awards

  1. Outstanding Teacher, Iowa State College of Liberal Arts and Sciences, 1998.
  2. Study in a Second Discipline (one semester release), Molecular Biology, Spring 2000.
  3. Vinograd Award for Excellence in Graduate Teaching in Mathematics, Spring 2003.
  4. Award for mid-career achievement in research, Iowa State University College of Liberal Arts and Sciences, 2004.
  5. Bioinformatics chair, University of Guelph, Department of Mathematics and Statistics, 2004.
  6. Senior Member of the IEEE, 2006.
  7. Best Theoretical Paper, Artificial Neural Networks in Engineering conference, for D. Ashlock, A. J. Shuttleworth, and K.M. Bryden, Induction of Virtual Sensors with Function Stacks, In Intelligent Engineering Systems Through Artificial Neural Networks, 19, PP 27-34, 2009.
  8. Best Paper, CEC 2011, D. Ashlock, E. Shiller, and C. Lee Comparison of Evolved Epidemic Networks with Diffusion Characters, Proceedings of IEEE Congress on Evolutionary Computation, PP 781-788, 2011.

Patents

  1. Creating real-time data driven music using context sensitive grammars and fractal algorithms, with Kris Bryden and Mark Bryden, 2007.

Publications

Journal Publications

  1. M. Timmins and D. Ashlock, Network Induction for Epidemic Profiles with a Novel Representation, conditionally accepted to Biosystems, 2017.
  2. D. Ashlock and A. McEachern, CliqeR: a Graph Theory Game, Game and Puzzle Design, Pages 42-50, 2017.
  3. D. Ashlock and C. McGuinness, Graph-Based Search for Game Design, Game and Puzzle Design, 2(2), PP 68-75, 2016.
  4. D. Ashlock, Graph Theory in Game and Puzzle Design, Game and Puzzle Design, 2(1), PP 62-70, 2016.
  5. E. Y. Kim and D. Ashlock, Changing Resources Available to Game Playing Agents: Another Relevant Design Factor in Agent Experiments, in press for the IEEE Transactions on Computational Intelligence and AI in Games, 2016.
  6. D. Ashlock and J. Schonfeld, Deriving Card Games from Mathematical Games, in Game and Puzzle Design, 1(2), PP 55-63, 2015.
  7. D. Ashlock and C. Lee, Influence Maps and New Versions of Risk, in Game and Puzzle Design, 1(1), PP 38-43, 2015.
  8. J. D. Phillips, R. A. Gwiazdowski, D. Ashlock, R. Hanner, An exploration of sufficient sampling effort to describe intraspecific DNA barcode haplotype diversity: examples from the ray-finned fishes (Chordata: Actinopterygii) in DNA Barcodes, Volume 3, PP 66-73, 2015.
  9. D. Ashlock and A. McEachern, Evolutionary Nonlinear Projection, IEEE Transactions on Evolutionary Computation, 19(6), PP 857-869, 2015.
  10. D. Ashlock, J. Brown, and P. Hingston, Multiple Opponent Optimization of Prisoner's Dilemma Playing Agents, in IEEE Transactions on Computational Intelligence and Artificial Intelligence in Games, pages 53-65, 2015.
  11. J. A. Huges Hughes, S. Houghten, D. Ashlock, Recentering and restarting a genetic algorithm using a generative representation for an ordered gene problem, International journal of hybrid intelligent systems, 11(4), PP257-271, 2014.
  12. P. Johnson, D. Ashlock, K. M. Bryden, A Novel Engineering Tool for Creative Design of Fluid Systems Engineering with Computers, Engineering with Computers, Volume 30(1), PP 15-29, 2014.
  13. A. McEachern, D. Ashlock, and J. Shonfeld, Sequence classification with side effect machines evolved via ring optimization, Biosystems, Volume 113(1), PP9-27, 2013.
  14. D. Ashlock, S. McNicholas, Fitness Landscapes of Evolved Cellular Automata, IEEE Transaction on Evolutionary Computation, volume 17(2), PP 198-212, 2013.
  15. D. Ashlock, C. Lee, Agent-Case Embeddings for the Analysis of Evolved Systems, IEEE Transaction on Evolutionary Computation, volume 17(2), PP 227-240, 2013.
  16. D. Ashlock, S. K. Houghten, J. A. Brown, and J. Orth, On the Synthesis of DNA Error Correcting Codes, Biosystems(110), pages 1-8, 2012.
  17. D. Ashlock, C. Lee, and C. McGuinness, Search-Based Procedural Generation of Maze-Like Levels, IEEE Transactions on Computational Intelligence and AI in Games, 3(3), PP 260-273, 2011.
  18. D. Ashlock, C. Lee, and C. McGuinness, Simultaneous Dual Level Creation for Games, IEEE Computational Intelligence Magazine, 6(2), PP 26-37, 2011. (Invited Publication).
  19. D. Ashlock, E. Clare, T. vonKonigslow, and W. Ashlock, Evolution and instability in ring species complexes: an in silico approach to the study of speciation, Journal of Theoretical Biology, 264(4), 1202-1213, 2010.
  20. E.Y. Kim, S.Y. Kim, D. Ashlock, D. Nam, MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering, BMC Bioinformatics, 10(260), PP1-12, doi:10.1186/1471-2105-10-260, 2009.
  21. D. Ashlock, E.Y. Kim, and W. Ashlock, Fingerprint Analysis of the Noisy Prisoner's Dilemma Using a Finite State Representation, IEEE Transactions on Computational Intelligence and AI in Games, 1(2), 157-167, 2009.
  22. D. S. Skibbe, X. Wang, L. A. Borsuk, D. A. Ashlock, D. Nettleton, and P. S. Schnable, Floret-specific differences in gene expression and support for the hypothesis that tapetal degeneration of Zea mays L. occurs via programmed cell death, Journal of Genetic and Genomics 35, PP 603-616, 2008.
  23. D. Ashlock and E.Y. Kim, Fingerprinting: Visualization and Analysis of Prisoner's Dilemma Strategies, IEEE Transactions on Evolutionary Computation, 12(5), 647-659, 2008.
  24. D. Ashlock and B. Jamieson, Evolutionary computation to search Mandelbrot sets for aesthetic images Journal of Mathematics and Art 1(3), PP 147-158, 2008.
  25. S. J. Emrich, L. Li, T. J. Wen, M. D. Yandeau-Nelson, Y. Fu, L. Guo, H. H. Chou, S. Aluru, D. A. Ashlock, P. S. Schnable, Nearly Identical Paralogs(NIPs): implications for maize(Zea Mays L.) genome evolution, Genetics 175(1), PP 429-439, 2006.
  26. A. L. Kaleita, B. L. Steward, R. P. Ewing, D. A. Ashlock, M. E. Westgate, J. L. Hatfield, Novel Analysis Of Hyperspectral Reflectance Data for Detecting Onset of Pollen Shed in Maize, in Transactions of the American Society of Agricultural and Biological Engineers, Vol. 49(6): 1947-1954, 2006.
  27. Y. Fu, T.J. Wen, Y.I. Ronin, H.D. Chen, L. Guo, D. Mester, Y. Yang, M. Lee, A. B. Korol, D. A. Ashlock, P. Schnable, Genetic Dissection of Intermated Recombinant Inbred Lines Using a New Genetic Map of Maize, in Genetics, 174:1671-1638, 2006
  28. D. Ashlock, E.Y. Kim, N. Leahy, Understanding Representational Sensitivity in the Iterated Prisoner's Dilemma with Fingerprints, in the Transactions on Systems, Man, and Cybernetics--Part C: Applications and Reviews, 36(4):464-475, 2006.
  29. K.M. Bryden, D. Ashlock, S. Corns, S. Willson, Graph Based Evolutionary Algorithms in the IEEE Transactions on Evolutionary Computation, 10(5):550-567,2005.
  30. Ding J, K Viswanathan, D Berleant, E Wurtele, D Ashlock, J. Dickerson, A Fulmer, PS Schnable PathBinderH: a tool for sentence-focused, plant taxonomy-sensitive access to the biological literature, Bioinformatics, 21:2560-2, 2005.
  31. S. J. Kirstukas, K. M. Bryden, and D. A. Ashlock, A Hybrid Evolutionary Strategy for the Analytical Solution of Differential Equations, in the International Journal of General Systems Design, 34(3), 279-299(2005).
  32. Hong Yao, Ling Guo, Yan Fu, Lisa A. Borsuk, Tsui-Jung Wen, David S. Skibbe, Xiangqin Cui1, Brian E. Scheffler, Jun Cao1, Scott J. Emrich, Daniel A. Ashlock, and Patrick S. Schnable, Evaluation of five ab initio gene prediction programs for the discovery of maize genes, in Plant Molecular Biology, Volume 57, Issue 3, Feb 2005, Pages 445 - 460
  33. Scott J. Emrich, Srinivas Aluru, Yan Fu, Tsui-Jung Wen, Mahesh Narayanan, Ling Guo, Daniel Ashlock, Patrick S. Schnable, A Strategy for Assembling the Maize (Zea mays L.) Genome, in BioInformatics Vol.20 no.2: 140-147, 2004.
  34. Timothy J. Close, Steve I. Wanamaker, Rico A. Caldo, Stacy M. Turner, Daniel A. Ashlock, Julie A. Dickerson, Rod A. Wing, Gary J. Muehlbauer, Andris Kleinhofs and Roger P. Wise, A New Resource for Cereal Genomics: 22K Barley GeneChip Comes of Age , in Plant Physiology Vol. 134:960-968, 2004.
  35. F. Qiu, L. Guo, T.J. Wen, D.A. Ashlock, P.S. Schnable, DNA Sequence-based Bar-codes for Tracking the Origins of ESTs from a maize cDNA Library Constructed using Multiple mRNA Sources, in Plant Physiology, 133: 475-481, 2003.
  36. Zhiqiang Chen, Ron M. Nelson, Daniel Ashlock, Comparison of Methods for Predicting Monthly Post Retrofit Energy Use in Buildings in the Transactions of ASHRAE, Volume 109, Part 2, 2003, Pages KC-03-2-3-1 to KC-03-2-3-10, 2003.
  37. Daniel Ashlock and James B. Goldin III, Chaos Automata: Iterated Function Systems with Memory, in Physica D. 181: 274-285, 2003.
  38. Kenneth M. Bryden, Daniel A. Ashlock, Douglas S. McCorkle, and Gregory L. Urban, Optimization of heat transfer utilizing graph based evolutionary algorithms, in the International Journal of Heat and Fluid Flow Volume 24, Issue 2: 267-277, 2003.
  39. Xiangqin Cui, An-Pin Hsia, Feng Liu, Daniel A. Ashlock, Roger P. Wise, Patrick Schnable, Alternative Transcription Initiation Sites and Polyadenylation Sites Are Recruited During Mu Supression at the rf2a Locus of Maize, in Genetics, Volume 163: 685-698, 2003.
  40. Dietrich C, F Cui, M Packila, D Ashlock, B Nikolau, PS Schnable, Maize Mu transposons are targeted to the 5' UTR of the gl8a gene and sequences flanking Mu target site duplications throughout the genome exhibit non-random nucleotide composition, in Genetics, 160: 697-716, 2002.
  41. G.L. Urban, K. M. Bryden, and D. A. Ashlock, Engineering Optimization of an Improved Plancha Stove, in Energy for Sustainable Development, Vol. VI, No. 2: 9-19, 2001.
  42. Richter, Charles W., Jr., Gerald Sheble, and Daniel Ashlock, Comprehensive Bidding Strategies with Genetic Programming/Finite State Automata, in -PWRS-0-10-1998, IEEE Transactions on Power Systems, Vol. 14, no. 4:1207-1212, 1999.
  43. Kenneth R. Driessel, Irvin Hentzel, and Daniel Ashlock, On Matrix Structures Invariant under Toda-like Isospectral Flows, in Linear Algebra and its Applications 254:29-48, 1997.
  44. E Ann Stanley, Daniel Ashlock, Leigh Tesfatsion, and Mark Smucker, Preferential Partner Selection in an Evolutionary Study of Prisoner's Dilemma, in Biosystems 37: 99-125, 1996
  45. Daniel Ashlock and David Schweizer, Graphical Construction of Cubic Cages, in Congressus Numerantium 112: 213-221, 1995.
  46. Daniel Ashlock and Jenette Tilliotson, Minimal Superpermutations, Congressus Numerantium 93: 91-98, 1993.
  47. Daniel Ashlock, Permutation Polynomials on Abelian Group Rings, in Journal of Pure and Applied Algebra 86:1-5, 1993.
  48. Daniel Ashlock, The Costas Invariant for Graphs, Congress Numerantium 90:7-14, 1992
  49. Daniel Ashlock, Compositional Attractors and Enumeration of Permutation Polynomials Over Finite Fields, Journal of Pure and Applied Algebra 81: 1-9, 1992.

Refereed Conference Publications

  1. J. A. Brown and D. Ashlock Using Multiple Worlds for Multiple Agent Roles in Games, in Proceedings of the 2017 IEEE Conference on Computational Intelligence in Games, Pages 1-8, 2017.
  2. D. Ashlock, D. P. Lebana, and A. Saunders General Video Game Playing Escapes the No Free Lunch Theorem, in Proceedings of the 2017 IEEE Conference on Computational Intelligence in Games, Pages 1-8, 2017.
  3. D. Ashlock and S. Houghten, Hybridization and Ring Optimization for Larger Sets of Embeddable Biomarkers, in the Proceedings of the 2017 IEEE Conference on Computational Intelligence in Bioiformatics and Computational Biology, Pages 1-8, 2017.
  4. G. A. Ruz, D. Ashlock, T. Ledger, and E. Goles Inferring bistable lac operon Boolean regulatory networks using evolutionary computation, in the Proceedings of the 2017 IEEE Conference on Computational Intelligence in Bioiformatics and Computational Biology, Pages 1-8, 2017.
  5. D. Ashlock and G. A. Ruz, A Novel Representation for Boolean Networks Designed to Enhance Heritability and Scalability, in the Proceedings of the 2017 IEEE Conference on Computational Intelligence in Bioiformatics and Computational Biology, Pages 1-8, 2017.
  6. D. Ashlock, S. Gillis, and W. Ashlock Infinite String Block Matching Features for DNA Classification, in the Proceedings of the 2017 IEEE Conference on Computational Intelligence in Bioiformatics and Computational Biology, Pages 1-8, 2017.
  7. D. Ashlock and W. Ashlock, A Note On Population Size Inspired By The Extinction Of Mammoths, in the Proceedings of the 2017 IEEE Conference on Computational Intelligence in Bioiformatics and Computational Biology, Pages 1-8, 2017.
  8. D. Ashlock and G. Greenwood, Modeling Undependable Subsidies with Three-player Generalized Divide the Dollar, in Proceedings of the 2017 IEEE Congress on Evolutionary Computation, PP 1335-1342, 2017.
  9. D. Ashlock and A. McEachern, Evolutionary Design of FRAX Decks, in Proccedings of the 2017 IEEE Congress on Evolutionary Computation, PP 994-951, 2017.
  10. J. Montgomery and D. Ashlock, Applying the Biased Form of the Adaptive Generative Representation, in Proccedings of the 2017 IEEE Congress on Evolutionary Computation, PP 1079-1086, 2017.
  11. D. Ashlock and L. Bickley, Rescalable, replayable maps generated with evolved cellular automata, Acta Physica Polonica (B), Proceedings Supplement, 9(1), PP 13-14, 2016.
  12. D. Ashlock and S. Graether, Conway Crossover to Create Hyperdimensional Point Packings, with Applications in Proceedings of the IEEE 2016 Congress on Evolutionary Computation, PP 1570-1577, 2016.
  13. D. Ashlock and G. Greenwood, Generalized Divide the Dollar in Proceedings of the IEEE 2016 Congress on Evolutionary Computation, PP 343-350, 2016.
  14. D. Ashlock and E. Y. Kim, The Impact of Elite Fraction and Population Size on Evolved Iterated Prisoner's Dilemma Agents in Proceedings of the IEEE 2016 Congress on Evolutionary Computation, PP 364-371, 2016.
  15. D. Ashlock and L. Taylor, Evolving Polyomino Puzzles in Proceedings of the IEEE 2016 Congress on Evolutionary Computation, PP 327-334, 2016.
  16. D. Ashlock and J. Montgomery, An Adaptive Generative Representation for Evolutionary Computation in Proceedings of the IEEE 2016 Congress on Evolutionary Computation, PP 1578-1585, 2016.
  17. D. Ashlock and S. Gillis, A. McEachern and J. Tsang , The Do What's Possible Representation in Proceedings of the IEEE 2016 Congress on Evolutionary Computation, PP 1586-1593, 2016.
  18. D. Ashlock and M. Timmins, Adding Local Edge Mobility to Graph Evolution in Proceedings of the IEEE 2016 Congress on Evolutionary Computation, PP 1594-1601, 2016.
  19. D. Ashlock and J. Brown, Evolutionary Partitioning Regression with Function Stacks in Proceedings of the IEEE 2016 Congress on Evolutionary Computation, PP 1469-1476, 2016.
  20. J. Gilbert and D. Ashlock, Evolvable Warps for Data Normalization in Proceedings of the IEEE 2016 Congress on Evolutionary Computation, PP 1562-1569, 2016.
  21. J. Tsang and D. Ashlock, The Impact of Obstruction on a Model of Competitive Exclusion in Plants Proccedings of the 2015 IEEE Symposium Series on Computational Intelligence, pages 1110-1117, 2015.
  22. D. Ashlock, Evolvable Fashion Based Cellular Automata for Generating Cavern Systems, in Proceedings of the 2015 IEEE Conference on Computatational Intelligence in Games, pages 306-313, 2015.
  23. D. Ashlock and S. Houghten, Lexicode Crossover for Embeddable Biomarkers, in Proccedings of the 2015 IEEE Conference on Computational Intelligence in Bioioinformatics and Comutational Biology, PP 1-7, 2015.
  24. M. Page and D. Ashlock, Stress and Productivity Performance in the Workforce Modelled with Binary Decision Automata, in Proceedings of the 2015 IEEE Conference on Computational Intelligence in Bioioinformatics and Comutational Biology, PP 1-8, 2015.
  25. L. Barlow and D. Ashlock, Varying Decision Inputs in Prisoner's Dilemma , in Proceedings of the 2015 IEEE Conference on Computational Intelligence in Bioioinformatics and Comutational Biology, PP 1-8, 2015.
  26. D. Ashlock, C. McGuinness and J. O'Neill, Interactive Evolution Instead of Default Parameters, in Proceedings of the 2015 IEEE Conference on Computational Intelligence in Bioioinformatics and Comutational Biology, PP 1-8, 2015.
  27. D. Ashlock and M. Timmins, A Comparison of Incremental Community Assembly with Evolutionary Community Selection, in Proceedings of the 2015 IEEE Conference on Computational Intelligence in Bioioinformatics and Comutational Biology, PP 1-8, 2015.
  28. D. Ashlock, S. Gillis, J. Garner, and G. Fogel, Evolving DNA Classifiers with Extinction Based Ring Optimization, in Proceedings of the 2015 IEEE Conference on Computational Intelligence in Bioioinformatics and Comutational Biology, PP 1-8, 2015.
  29. D. Ashlock, C. McGuinness, and W. Ashlock Chaos Automata for Sequence Visualization, in Proceedings of the the 2015 IEEE Conference on Computational Intelligence in Bioioinformatics and Comutational Biology, PP 1-8, 2015.
  30. D. Ashlock and J. Tsang, Evolving Fractal Art with a Directed Acyclic Graph Genetic Programming Representation, Proceedings of the 2015 Congress on Evolutionary Computation, PP 2137-2144, 2015.
  31. J. Garner and D. Ashlock Evolution of 2D Apoptotic Cellular Automata, Proceedings of the 2015 Congress on Evolutionary Computation, PP 2160-2167, 2015.
  32. J. Schonfeld and D. Ashlock Flow of Control in Linear Genetic Programming, Proceedings of the 2015 Congress on Evolutionary Computation, PP 1175-1182, 2015.
  33. D. Ashlock, S. Gillis, and G. Fogel Ring Optimization with Extinction, Proceedings of the 2015 Congress on Evolutionary Computation, PP 1311-1318, 2015.
  34. D. Ashlock and L. Barlow A Class of Representations for Evolving Graphs, Proceedings of the 2015 Congress on Evolutionary Computation, PP 1295-1302, 2015.
  35. D. Ashlock, P. Hingston, and C. McGuinness Evolving Point Packing in the Plane, Proceedings of the Australasian Conference on Artificial Live and Computational Intelligence, PP. 297-309, 2015.
  36. D. Ashlock and J. Gilbert, A Discrete Representation for Real Optimization with Unique Search Properties, Proceedings of the IEEE Symposium on the Foundations of Computational Intelligence, PP 54-61, 2014.
  37. D. Ashlock, J. Schonfeld, L. Barlow and C. Lee, Test Problems and Representations for Graph Evolution, Proccedings of the IEEE Symposium on the Foundations of Computational Intelligence, PP 38-45, 2014.
  38. W. Ashlock, J. Tsang, and D. Ashlock, The Evolution of Exploitation, Proceedings of the IEEE Symposium on the Foundations of Computational Intelligence, PP 135-142, 2014.
  39. D. Ashlock and C. McGuinness, Automatic Generation of Fantasy Role-playing Modules, Proceedings of the IEEE Conference on Computatiational Inteligence in Games, PP 60-67, 2014.
  40. W. Ashlock and D. Ashlock, Shaped Prisoner's Dilemma Automata, Proceedings of the IEEE Conference on Computatiational Inteligence in Games, PP 76-83, 2014.
  41. J.Hughes, S.Houghten and D.Ashlock, Recentering, Reanchoring and Restarting an Evolutionary Algorithm, 5th World Congress on Nature and Biologically Inspired Computing, p.76-83, 2013.
  42. D. Ashlock and A. Goren, Agent-based Modelling of Resource Flow in Plant Networks, in Proceedings of the 2013 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, PP 1-8, 2014
  43. D. Ashlock and E. Y. Kim, Using Associators To Generate Ensemble Biclustering From Multiple Evolved Biclusterings, in Proceedings of the 2013 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, PP 1-8, 2014
  44. A. McEachern and D. Ashlock, Shape Control of Side Effect Machines for DNA Classification in Proceedings of the 2013 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, PP 1-8, 2014
  45. J. Hughes, S. Houghten, G. Mallen-Fullerton and D. Ashlock Recentering and Restarting Genetic Algorithms Variations for DNA Fragment Assembly in Proceedings of the 2013 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, PP 1-8, 2014.
  46. D. Ashlock and C. McGuinness, Landscape Automata for Search Based Procedural Content Generation, in Proceedings of the 2013 IEEE Conference on Computational Intelligence in Games, PP 9-16, 2013.
  47. D. Ashlock and J. Gilbert, Creativity and Competitiveness in Polyomino-Developing Game Playing Agents in Proceedings of the 2013 IEEE Conference on Computational Intelligence in Games, PP 249-256, 2013.
  48. L. A. Barlow and D. Ashlock, The Impact of Connection Topology and Agent Size on Cooperation in the Iterated Prisoner's Dilemma in Proceedings of the 2013 IEEE Conference on Computational Intelligence in Games, PP 299-306, 2013.
  49. H. James, S. Houghten, and D. Ashlock, Recentering, reanchoring & restarting an evolutionary algorithm, in Proceedings of the 2013 World Congress on Nature and Biologically Inspired Computing (NaBIC), PP 76-83, 2013.
  50. M. Page and D. Ashlock, Binary Decision Automata Modelling Stress in the Workplace, Proceedings of the 2013 Congress on Evolutionary Computation, PP 3331-3338, 2013.
  51. D. Ashlock and C. Pugh, Evolutionary Cellular Automata Bonsai, Proceedings of the 2013 Congress on Evolutionary Computation, PP 325-332, 2013.
  52. D. Ashlock, N. Krisk, and G. Fogel, Functions for the Analysis of Exploration and Exploitation, Proceedings of the 2013 Congress on Evolutionary Computation, PP 2020-2027, 2013.
  53. A. McEachern and D. Ashlock, Woven String Kernels for DNA Sequence Classification Proceedings of the 2013 Congress on Evolutionary Computation, PP 1578-1585, 2013.
  54. J. Hughes, J. Brown, S. Houghten and D. Ashlock, Edit Metric Decoding: Representation Strikes Back, Proceedings of the 2013 Congress on Evolutionary Computation, PP 229-236, 2013.
  55. D. Ashlock and E. Shiller, Evolving a social fabric to fit an epidemic profile, Proceedings of the 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP 363-370, 2012.
  56. D. Ashlock and E. Wild, A model of competitive exclusion in plants, Proceedings of the 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP 206-213, 2012.
  57. D. Ashlock and E. Y. Kim, The Impact of Varying Resources Available to Iterated Prisoner's Dilemma Agents Proceedings of FOCI 2013, PP 60-67.
  58. D. Ashlock and M. Page, An Agent Based Model of Stress in the Workplace Proceedings of EAIS 2013, PP 114-121.
  59. D. Ashlock and E. Knowles, Deck-Based Prisoner's Dilemma, Proceedings of the IEEE 2012 Conference on Computational Intelligence in Games, PP 17-24, 2012.
  60. D. Ashlock, W. Ashlock, S. Samothrakis, S. Lucas, and C. Lee From Competition to Cooperation: Co-evolution In A Rewards Continuum, proceedings of the IEEE 2012 Conference on Computational Intelligence in Games, PP 33-40, 2012.
  61. D. Ashlock and W. Ashlock, Impact of Regulatory Genes on Optimization Behavior, Proceedings of the 2012 IEEE Congress on Evolutionary Computation, PP 3372-3379, 2012.
  62. D. Ashlock and S. McNicholas, Single Parent Generalization of Cellular Automata Rules, Proceedings of the 2012 IEEE Congress on Evolutionary Computation, PP 179-186, 2012.
  63. G. Greenwood and D. Ashlock, Evolutionary Games and the Study of Cooperation: Why Has So Little Progress Been Made?, Proceedings of the 2012 IEEE Congress on Evolutionary Computation, PP 680-687, 2012.
  64. D. Ashlock and S. Nguyen, Financial Control of the Evolution of Autonomous NPCs, Proceedings of IEEE Congress on Evolutionary Computation, PP 823-835, 2011.
  65. D. Ashlock, C. Kuusela, and M. Cojocaru Shopkeeper Strategies in the Iterated Prisoner's Dilemma,, Proceedings of IEEE Congress on Evolutionary Computation, PP 1063-1070, 2011.
  66. D. Ashlock and C. McGuinness Decomposing the Level Generation Problem with Tiles, Proceedings of IEEE Congress on Evolutionary Computation, PP 849-856, 2011.
  67. D. Ashlock and J. Brown Fitness Functions for Searching the Mandelbrot Set, Proceedings of IEEE Congress on Evolutionary Computation, PP 1108-1115, 2011.
  68. D. Ashlock, J. Schonfeld and P. McNicholas Translation Tables: A Genetic Code in an Evolutionary Algorithm, Proceedings of IEEE Congress on Evolutionary Computation, PP 2685-2692, 2011.
  69. J. Brown, D. Ashlock, S. Houghten and J. Orth Autogeneration of Fractal Photographic Mosaic Images, Proceedings of IEEE Congress on Evolutionary Computation, PP 1116-1123, 2011.
  70. D. Ashlock, E. Shiller, and C. LeeComparison of Evolved Epidemic Networks with Diffusion Characters, Proceedings of IEEE Congress on Evolutionary Computation, PP 781-788, 2011.
  71. J. Brown and D. Ashlock, Domination in Iterated Prisoner's Dilemma, Proceedigns of CCECE 2011, PP 1125-1128, 2011.
  72. D. Ashlock and E. Shiller Fitting Contact Networks to Epidemic Behavior with an Evolutionary Algorithm, Proceedings of CIBCB 2011, PP 1-8, 2011.
  73. D. Ashlock and A. McEachern A Simulation of Bacterial Communities, Proceedings of CIBCB 2011, PP 1-8, 2011.
  74. W. Ashlock and D. Ashlock Designing Artificial Organisms For Use In Biological Simulations, Proceedings of CIBCB 2011, PP 1-8, 2011.
  75. A. Ashlock, C. Kuusela, N. Rogers, Hormonal systems for prisoners dilemma agents, Proceedings of CIG 2011, PP 63-70, 2011.
  76. C. McGuinness and D. Ashlock, Incorporating required structure into tiles, Proceedings of CIG 2011, PP 16-23, 2011.
  77. D. A. Ashlock, J. A. Brown, and S. M. Corns, K-models Clustering, a Generalization of K-means Clustering, Intelligent Engineering Systems Through Artificial Neural Networks(20), PP 485-492, 2010.
  78. J. A. Brown and D. A. Ashlock, Using Evolvable Regressors to Partition Data, Intelligent Engineering Systems Through Artificial Neural Networks(20), PP 187-194, 2010.
  79. D. Ashlock, Automatic Generation of Game Elements via Evolution, Proceedings of the 2010 IEEE Conference on Computational Intelligence in Games, 289-296, 2010.
  80. D. Ashlock and E.Y. Kim, Prisoner's Dilemma: the Payoff Values Matter, Proceedings of the 2010 IEEE Conference on Computational Intelligence in Games, PP 219-226, 2010.
  81. D. Ashlock and J. Schonfeld, Evolution for Automatic Assessment of the Difficulty of Sokoban Boards, Proceedings of the 2010 IEEE Congress on Evolutionary Computation, PP 2179-2186, 2010.
  82. W. Ashlock and D. Ashlock, Virtual retroviruses in grid walkers: effects on genome organization, Proceedings of the 2010 IEEE Congress on Evolutionary Computation, PP 4616-4623, 2010.
  83. D. Ashlock and A. McEachern, Nearest Neighbor Training of Side Effect Machines for Sequence Classification, in Proceedings of the 2010 IEEE Symposium on Bioinformatics and Computational Biology, PP 111-118, 2010.
  84. D. Ashlock and J. Schonfeld, Classifying Cytochrome C Oxidase Subunit 1 by Translation Initiation Mechanism using Side Effect Machines, in Proceedings of the 2010 IEEE Symposium on Bioinformatics and Computational Biology, 262-268, 2010.
  85. J. Brown, S. Hougthen and D. Ashlock, Side Effect Machines for Quaternary Edit Metric Decoding, to in the Proceedings of the 2010 IEEE Symposium on Bioinformatics and Computational Biology, PP 103-110, 2010.
  86. J. A. Brown, S. K. Houghten, D. A. Ashlock, Edit Metric Decoding: A New Hope in Proceedings of the 2nd Canadian Conference on Computer Science and Software Engineering, PP 233-242, 2009.
  87. D. Ashlock, T. vonKonigslow, and J. Schonfeld, Breaking a Hierarchical Clustering Algorithm with an Evolutionary Algorithm, In Intelligent Engineering Systems Through Artificial Neural Networks, 19, PP 197-204, 2009.
  88. D. Ashlock, A. J. Shuttleworth, and K.M. Bryden, Induction of Virtual Sensors with Function Stacks, In Intelligent Engineering Systems Through Artificial Neural Networks, 19, PP 27-34, 2009.
  89. D. Ashlock, K.M. Bryden, and S. Gent, Multiscale Feature Location with a Fractal Representation,In Intelligent Engineering Systems Through Artificial Neural Networks, 19, PP 173-180, 2009.
  90. D. Ashlock, K.M. Bryden, and D. McCorkle, Logic Function Induction with the Blender Algorithm using Function Stacks,In Intelligent Engineering Systems Through Artificial Neural Networks, 19, PP 189-196, 2009.
  91. D. Ashlock and A. McEachern, Ring Optimization of Side Effect Machines, In Intelligent Engineering Systems Through Artificial Neural Networks, 19, PP 165-172, 2009.
  92. D. Ashlock, K.M. Bryden, and S. M. Corns, Taxonomy of a Diverse Collection of String Optimization Problems, In Intelligent Engineering Systems Through Artificial Neural Networks, 19, PP 181-188, 2009.
  93. D. Ashlock and N. Rogers, The Imapact of Long Term Memory in the Iterated Prisoner's Dilemma, In Intelligent Engineering Systems Through Artificial Neural Networks, 19, PP 245-252, 2009.
  94. D. Ashlock, J. Schonfeld, J. Humphrey, Robustness in Evolved Grid Structures in Proceedings of the 2009 Congress on Evolutionary Computation, PP 1343-1350, 2009.
  95. D. Ashlock and J. Tsang, Evolved Art via Control of Cellular Automata in Proceedings of the 2009 Congress on Evolutionary Computation, PP 3338-3344, 2009.
  96. D. Ashlock and T. VonKonigslow, Diagnostic Character Location within the Cryptic Skipper Butterfly Species Complex with an Evolutionary Algorithm, in Proceedings of the 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP 92-99, 2009.
  97. D. Ashlock and W. Ashlock, Simulation of the Impact of Retroviruses on Genome Organization of an Artificial Organism, in Proceedings of the 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP 140-147, 2009.
  98. D. Ashlock and C. Lee, Using Diffusion Characters for the Taxonomy of Self-Organizing Social Networks, in Proceedings of the 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP 60-67, 2009.
  99. D. Ashlock and S. Houghten, Title: DNA Error Correcting Codes: No Crossover, in Proceedings of the 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP 38-45, 2009.
  100. D. Ashlock, T. VonKonigslow, E. Clare and W. Ashlock, Transience in the Simulation of Ring Species, Proccedings of the 2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP 256-263, 2008.
  101. D. Ashlock and C. Lee, Characterization of Extremal Epidemic Networks with Diffusion Characters Proccedings of the 2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP 264-271, 2008.
  102. D. Ashlock and N. Rogers, A Model of Emotion in the Prisoner's Dilemma Proceedings of the 2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP 272-279, 2008.
  103. D. Ashlock and E. Warner, Classifying Synthetic and Biological DNA Sequences with Side Effect Machines Proceedings of the 2008 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP 22-29, 2008.
  104. D. A. Ashlock, K. M. Bryden, and S. Corns Small Population Effects and Hybridization, in Proceedings of the 2008 Congress on Evolutionary Computation, PP 2642-2648, 2008.
  105. D. A. Ashlock and E. Warner, The Geometry of Tartarus Fitness Cases, in Proceedings of the 2008 Congress on Evolutionary Computation, PP 1309-1316, 2008.
  106. D. A. Ashlock and F. Jafargholi, Behavioral Regimes in the Evolution of Extremal Epidemic Graphs, in Proceedings of the 2008 Congress on Evolutionary Computation, PP 660-667, 2008.
  107. D. A. Ashlock and T. von Konigslow, Evolution of Artifical Ring Species, in Proceedings of the 2008 Congress on Evolutionary Computation, PP 653-659, 2008.
  108. D. Ashlock and E. Warner, Side Effect Machines for Sequence Classification, in Proceedings of the Canadian Conference on Electrical & Computer Engineering 2008, PP 1453-1456, 2008.
  109. C. Lee and D. Ashlock, Diffusion Characters: Breaking the Spectral Barrier, in Proceedings of the Canadian Conference on Electrical & Computer Engineering 2008, PP 847-850, 2008.
  110. D. A. Ashlock and J. Schonfeld, A Fractal Representation for Real Optimization, in Proceedings of the 2007 Congress on Evolutionary Computation, PP 87-94, 2007.
  111. D. A. Ashlock and E.Y. Kim, Fingerprint Analysis of the Noisy Prisoner's Dilemma, in Proceedings of the 2007 Congress on Evolutionary Computation, PP 4073-4080, 2007.
  112. D. Ashlock and B. Jamieson, Evolutionary Exploration of Generalized Julia Sets in the Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Signal Processing, PP 163-170, 2007.
  113. D. Ashlock, Cooperation in Prisoner's Dilemma on Graphs in the Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Games, PP 48-55, 2007.
  114. D. Ashlock and F. Jafargholi, Evolving Extremal Epidemic Networks in the Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP 338-345.
  115. D. Ashlock and L. Guo, Evolutionary Parameter Setting of Multi-clustering in the Proceedings of the 2007 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP 25-31, 2007.
  116. S. M. Corns, H. S. Hurd, D. Ashlock and K.M. Bryden, Evolutionary Optimization of an Antibiotic Feed Regimen Applied to Multiple Bacteria, in Intelligent Engineering Systems Through Artificial Neural Networks, Vol 16, PP. 255-260, 2007.
  117. D. Ashlock and K.M. Bryden, Function Stacks, GBEAs, and Crossover for the Parity Problem, in Intelligent Engineering Systems Through Artificial Neural Networks, Vol 16, PP 109-118, 2007.
  118. S. M. Corns, K.M. Bryden, and D.A. Ashlock Takeover Times in Graph Based Evolutionary Algorithms, in Intelligent Engineering Systems Through Artificial Neural Networks, Vol 16, PP 119-124.
  119. D. Ashlock, K.M. Bryden, and N. G. Johnson, Evolvable Threaded Controllers for a Multi-agent Grid Robot Task, in Intelligent Engineering Systems Through Artificial Neural Networks, Vol 16, PP 137-142, 2007.
  120. D. Ashlock and K.M. Bryden, Breeding Schedules Improve Grid Robot Performance, in Intelligent Engineering Systems Through Artificial Neural Networks, Vol 16, PP 143-148, 2007.
  121. D. Ashlock, K.M. Bryden, and A. Toole Obstructed Tartarus: Generalizing a Grid Robot Task, in Intelligent Engineering Systems Through Artificial Neural Networks, Vol 16, PP 149-154, 2007.
  122. B. Karthikeyan. D. Ashlock, and K.M. Bryden, A New Image Quality Metric for Evolver, Weighted Voronoi Image Segments, in Intelligent Engineering Systems Through Artificial Neural Networks, Vol 16, PP. 433-438, 2007.
  123. S. Corns, S. Hurd, D. Ashlock and K. M. Bryden, Developing Antibiotic Regimens Using Graph Based Evolutionary Algorithms in Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP. 476-481, 2006.
  124. J. Schonfeld and D. Ashlock, Filtration and Depth Annotation Improve Non-linear Projection for RNA Motif Discovery, in Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP 352-359, 2006.
  125. D. Ashlock, K. Cottenie, L. Carson, K.M. Bryden, and S. Corns, An Evolutionary Algorithm for the Selection of Geographically Informatics Species, in Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP 279-285, 2006.
  126. D. Ashlock, W. Ashlock and G. Umphrey, An Exploration of Differential Utility in Iterated Prisoner's Dilemma, in Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, PP 271-278, 2006.
  127. D. Ashlock, Evolutionary Exploration of the Mandelbrot Set in the Proceedings of the 2006 Congress On Evolutionary Computation, pages 7432-7439, 2006.
  128. J. Schonfeld and D. Ashlock, Evaluating Distance Measures for RNA Motif Search, in the Proceedings of the 2006 Congress On Evolutionary Computation, pages 8095-8102, 2006.
  129. N. Johnson, B. Karthikeyan, D. Ashlock and K. Bryden, AMoEBA Image Segmentation: Modeling of Individual Voronoi Tessellations, in the Proceedings of the 2006 Congress On Evolutionary Computation, pages 7480-7486, 2006.
  130. S. Corns, D. Ashlock, D. McCorkle and K. BrydenImproving Design Diversity Using Graph Based Evolutionary Algorithms, in the Proceedings of the 2006 Congress On Evolutionary Computation, pages 1037-1043, 2006.
  131. S. Gent, D. Ashlock, A. Willms and K. Bryden, Generalized Thermal Agents with Multiple Boundary Conditions and Three-Dimensional Thermal Agents, in the Proceedings of the 2006 Congress On Evolutionary Computation, pages 10935-10942, 2006.
  132. W. Ashlock and D. Ashlock, Changes in Prisoner's Dilemma Strategies Over Evolutionary Time With Different Population Sizes, in the Proceedings of the 2006 Congress On Evolutionary Computation, pages 1001-1008, 2006.
  133. D. Ashlock, K. Bryden, S. Corns and J. Schonfeld An Updated Taxonomy of Evolutionary Computation Problems using Graph-based Evolutionary Algorithms, in the Proceedings of the 2006 Congress On Evolutionary Computation, pages 403-410, 2006.
  134. D. Ashlock, T. Manikas and K. Ashenayi, Evolving A Diverse Collection of Robot Path Planning Problems, in the Proceedings of the 2006 Congress On Evolutionary Computation, pages 6728-6735, 2006.
  135. D. Ashlock, K. Bryden and S. Gent, Simultaneous Evolution of Bracketed L-system Rules and Interpretation, in the Proceedings of the 2006 Congress On Evolutionary Computation, pages 7403-7410, 2006.
  136. D. Ashlock, B. Karthikeyan and K. Bryden Non-photorealistic Rendering of Images as Evolutionary Stained Glass, in the Proceedings of the 2006 Congress On Evolutionary Computation, pages 7440-7447, 2006.
  137. D. Ashlock, Training Function Stacks to Play Iterated Prisoner's Dilemmain the Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Games, pages 111-118, 2006.
  138. D. Ashlock, Grid-Robot Drivers: an Evolutionary Multi-agent Virtual Robotics Task, in the Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Games, pages 19-26, 2006.
  139. S. Suram, D. S. McCorkle, D. A. Ashlock, K. M. Bryden, Modeling Tracking Behavior with Virtual Autonomous Agents, in Proceedings of the Seventh International Conference in Adaptive Computing in Design and Manufacture, 121-127, 2006.
  140. D. A. Ashlock, J. Schoenfeld, E. Kim, and K. M. Bryden, Fitness Webs for Analysis of Braitenberg Vehicles, in Proceedings of the Seventh International Conference in Adaptive Computing in Design and Manufacture, 109-119, 2006.
  141. D. A. Ashlock, S. P. Gent, and K. M. Bryden, Thermal Agents: Learning Harder Thermal Profiles, Proceedings of the Seventh International Conference in Adaptive Computing in Design and Manufacture, 53-60, 2006.
  142. D. A. Ashlock, A. Willms, S. P. Gent, and K. M. Bryden, Rapid Training of Thermal Agents with Gradient Single Parents, Proceedings of the Seventh International Conference in Adaptive Computing in Design and Manufacture, 191-198, 2006.
  143. B. Karthikeyan, K. M. Bryden, D. A. Ashlock, Interactive Engineering Decision Making Using Image Segmentation and Quality Assessment, Proceedings of the Seventh International Conference in Adaptive Computing in Design and Manufacture, pp. 279-283, 2006.
  144. D. A. Ashlock and J. Schonfeld, Depth Annotation of RNA Folds for Secondary Structure Motif Search, Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, pages 38-45, 2005.
  145. D. A. Ashlock and S. Houghten, A Novel Variation Operator for More Rapid Evolution of DNA Error Correcting Codes, Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, pages 53-60, 2005.
  146. D. A. Ashlock, R. Swanson, and P. S. Schnable, Selection of Genetically Diverse Recombinant Inbreds with and Ordered Gene Evolutionary Algorithm, Proceedings of the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, pages 237-242, 2005.
  147. D. A. Ashlock, K. M. Bryden, and S. P. Gent, Evolving L-systems to Locate Edit Metric Codes, in Smart Engineering System Design: Neural Networks, Fuzzy, Evolutionary Programming, and Artificial Life, edited by C. H. Dagli et al., ASME Press, 15:201-209 , 2005.
  148. D. A. Ashlock and K. M. Bryden, Non-Local Adaptation in Bidding Agents, in Smart Engineering System Design: Neural Networks, Evolutionary Programming, and Artificial Life, edited by C. H. Dagli et al., ASME Press, 15:193-199 , 2005.
  149. S. M. Corns, K. M. Bryden, and D. A. Ashlock, The Impact of Novel Connection Topologies on Graph Based Evolutionary Algorithms, in Smart Engineering System Design: Neural Networks, Evolutionary Programming, and Artificial Life, edited by C. H. Dagli et al., ASME Press, 15:201-209 , 2005.
  150. K. M. Bryden, D. A. Ashlock, and B. Karthikeyan. Low-Impact Image Segmentation by Balanced Weighted Voronoi Tessellations, in Smart Engineering System Design: Neural Networks, Evolutionary Programming, and Artificial Life, edited by C. H. Dagli et al., ASME Press, 15:533-541 , 2005.
  151. D. A. Ashlock, K. M. Bryden, and S. P. Gent. Creating Spatially Constrained Virtual Plants Using L-Systems, in Smart Engineering System Design: Neural Networks, Evolutionary Programming, and Artificial Life, edited by C. H. Dagli et al., ASME Press, 15:185-192 , 2005.
  152. D. A. Ashlock, E.Y. Kim, and L. Guo. Multi-clustering: avoiding the natural shape of underlying metrics, in Smart Engineering System Design: Neural Networks, Evolutionary Programming, and Artificial Life, edited by C. H. Dagli et al., ASME Press, 15:453-461 , 2005.
  153. S. Corns, K. Bryden, D. Ashlock and D. Muth On the Effects of Representation on Evolving Grid Robot, Proceedings of the 2005 Congress on Evolutionary Computation, pages 1135-1140, 2005.
  154. D. Ashlock, K. M. Bryden, and S. Corns, Graph Based Evolutionary Algorithms Enhance the Location of Steiner Systems, Proceedings of the 2005 Congress on Evolutionary Computation, Vol. 2, pages 1861-1866, 2005.
  155. Daniel Ashlock, Kenneth M. Bryden, Wendy Ashlock, and Stephen P. Gent, Rapid Training of Thermal Agents with Single Parent Genetic Programming, Proceedings of the 2005 Congress on Evolutionary Computation,Vol. 3, pages 2122-2129, 2005.
  156. Wendy Ashlock and Daniel Ashlock, Single Parent Genetic Programming, Proceedings of the 2005 Congress on Evolutionary Computation, Vol 2, pages 1172-1179, 2005.
  157. Daniel Ashlock and Adam Sherk, Non-local Adaptation of Artificial Predators and Prey, Proceedings of the 2005 Congress on Evolutionary Computation, Vol. 1, pages 41-48, 2005.
  158. Daniel Ashlock and Justin Schonfeld, Nonlinear Projection for the Display of High Dimensional Distance Data, Proceedings of the 2005 Congress on Evolutionary Computation, Vol. 3, pages 2776-2783, 2005.
  159. Daniel Ashlock, Stephen P. Gent, and Kenneth M. Bryden, Evolution of L-systems for Compact Virtual Landscape Generation, Proceedings of the 2005 Congress on Evolutionary Computation, Vol. 3, pages 2760-2767, 2005.
  160. Daniel Ashlock and Eun-Youn Kim, Techniques for Analysis of Evolved Prisoner's Dilemma Strategies with Fingerprints., Proceedings of the 2005 Congress on Evolutionary Computation, Vol 3, pages 2613-2620, 2005.
  161. Justin Schonfeld and Daniel Ashlock, A Study of Evolutionary Robustness in Stochastically Tiled Polyominos. Proceedings of the 2005 Genetic and Evolutionary Computation Conference, pages 19-26.
  162. Daniel Ashlock and Eun-Youn Kim, The Impact of Cellular Representation on Finite State Agents for Prisoner's Dilemma, Proceedings of the 2005 Genetic and Evolutionary Computation Conference, pages 59-66, 2005.
  163. D. A. Ashlock, K. M. Bryden, S. Corns, P. S. Schnable and T.J. Wen, Training Finite State Classifiers to Improve PCR Primer Design, Proceedings of the 10th Annual AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Albany, NY, 2004.
  164. Daniel A. Ashlock, Kenneth M. Bryden, and Douglas McCorkle, Multi-deme Planned Tournament Selection, in Intelligent Engineering Systems Through Artificial Neural Networks, Vol 14:217-221, 2004.
  165. Peter G. Anderson and Daniel A. Ashlock, Advances in Ordered Greed, in Intelligent Engineering Systems Through Artificial Neural Networks, Vol 14:223-228, 2004.
  166. Dan Ashlock, Kenneth M. Bryden, Steven Corns, and Stephen J. Willson, A Taxonomy of Evolutionary Computation Problems, in Intelligent Engineering Systems Through Artificial Neural Networks, Vol 14:235-240, 2004.
  167. Steven J. Kirstukas, Kenneth M. Bryden, and Daniel A. Ashlock, A Genetic Programming Technique for Solving Systems of Differential Equations, in Intelligent Engineering Systems Through Artificial Neural Networks, Vol 14:241-246, 2004.
  168. Aaron N. Bryden, Kris A. Bryden, and Daniel A. Ashlock, Presenting a large audience interactive multimedia performance driven by a circular Lindenmayer system, in Intelligent Engineering Systems Through Artificial Neural Networks, Vol 14:253-258, 2004.
  169. Dan Ashlock, Kenneth M. Bryden, and Stephen Patrick Gent, Evolutionary Control of Bracked L-system Interpretation, in Intelligent Engineering Systems Through Artificial Neural Networks, Vol 14:271-276, 2004.
  170. Brian L. Steward, Robert P. Ewing, Daniel A. Ashlock, Amy L. Kaleita, and Steve M. Shaner, Range Operator Enhanced Genetic Algorithms fir Hyperspectral Analysis, in Intelligent Engineering Systems Through Artificial Neural Networks, Vol 14:295-300, 2004.
  171. Peter E. Johnson, Kenneth M. Bryden, and Daniel A. Ashlock, Using Evolutionary Data Segregation Techniques to Reduce the Computation Time Needed to Design Piping Flow using CFD, in Intelligent Engineering Systems Through Artificial Neural Networks, Vol 14:433-438, 2004.
  172. D. A. Ashlock, S. J. Emrich, K. M. Bryden, S.M. Corns, T.J. Wen, and P. S. Schnable, A Comparison of Evolved Finite State Classifiers and Interpolated Markov Models for Improving PCR Primer Design,in the Proceedings of the 2004 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB '04): 190-197, 2004.
  173. Dan Ashlock and Kenneth M. Bryden, Evolutionary Control of L-system Interpretation, in Proceedings of the 2004 Congress on Evolutionary Computation, Vol 2:2273-2279, 2004.
  174. Sunil Suram, Kenneth M. Bryden, and Daniel Ashlock, Quantitative Trait Loci base Solution of an Inverse Radiation Heat Transfer Problem, in Proceedings of the 2004 Congress on Evolutionary Computation, Vol 1:427-432, 2004.
  175. Daniel Ashlock, Stephen Willson and Nicole Leahy, Coevolution and Tartarus, in Proceedings of the 2004 Congress on Evolutionary Computation, Vol 2:1618-1624, 2004.
  176. Daniel Ashlock, Eun-youn Kim and Warren vonRoeschlaub, Fingerprints: Enabling Visualization and Automatic Analysis of Strategies for Two Player Games, in Proceedings of the 2004 Congress on Evolutionary Computation, Vol 1:381-387, 2004.
  177. Daniel Ashlock, Kenneth Bryden and Steven Corns, On Taxonomy of Evolutionary Computation Problems, in Proceedings of the 2004 Congress on Evolutionary Computation, Vol 2:1713-1719, 2004.
  178. Dan Ashlock and Brad Powers, The Effect of Tag Recognition on Non-Local Adaptation, in Proceedings of the 2004 Congress on Evolutionary Computation, Vol2:2045-2051.
  179. Daniel Ashlock and James Lathrop, Program Induction: Building a Wall, in Proceedings of the 2004 Congress on Evolutionary Computation, Vol 2:1844-1850, 2004.
  180. Dan Ashlock and Jessica Oftelie, Simulation of Floral Specialization in Bees, in Proceedings of the 2004 Congress on Evolutionary Computation, Vol 2:1859-1864.
  181. Justin Schonfeld and Dan Ashlock, Comparison of Robustness of Solutions Located by Evolutionary Computation and Other Search Algorithms, in Proceedings of the 2004 Congress on Evolutionary Computation, Vol 1:250-257, 2004.
  182. Kenneth Bryden, Daniel Ashlock and Douglas McCorkle, An Application of Graph Based Evolutionary Algorithms for Diversity Preservation, in Proceedings of the 2004 Congress on Evolutionary Computation, Vol 1:419-426.
  183. Dan Ashlock and Nicole Leahy, A Representational Study of Game Theoretic Simulations, in SMCia/03: Proceedings of the 2003 IEEE Conference on Soft Computing in Industrial Applications:67-72, 2003.
  184. Dan Ashlock, Dean C. Adams, David Doty, Morphometric Grayscale Texture Analysis using Foot Patterns, in Proceedings of the 2003 Congress on Evolutionary Computation:1575-1581, 2003.
  185. Dan Ashlock, Elizabeth Blankenship, Jonathan D. Gandrud, A Note on General Adaptation in Populations of Painting Robots, in Proceedings of the 2003 Congress on Evolutionary Computation: 46-53, 2003.
  186. Dan Ashlock and Kenneth M. Bryden, Thermal Agents: An Application of Genetic Programming to Virtual Engineering, in Proceedings of the 2003 Congress on Evolutionary Computation: 1340-1347, 2003.
  187. Douglas S. McCorkle, Kenneth M. Bryden, Daniel A. AshlockPlanned Tournament Selection, Proceedings of ANNIE: 385-390, 2003.
  188. Balu Karthikeyan, Kenneth M. Bryden, Daniel A. Ashlock, Visualizing Information Flow in Evolving Graph-based Population, Proceedings of ANNIE:299-305, 2003.
  189. Peter E. Johnson, Kenneth M. Bryden, Daniel A. Ashlock, Solution of a 2-D Inverse Heat Conduction Problem Using Evolutionary Data Segregation Techniques, Proceedings of ANNIE:315-320, 2003.
  190. Steven M. Corns, Kenneth M. Bryden, Daniel A. Ashlock,Rate of Information Transfer in Graph Based Evolutionary Algorithms, Proceedings of ANNIE:261-266, 2003.
  191. Kenneth M. Bryden and Daniel A. Ashlock, Thermal Agents: Learning Thermal Profiles for Rapid Design, Proceedings of ANNIE:939-945, 2003.
  192. Steven M. Corns, Kenneth M. Bryden, Daniel A. Ashlock, Evolutionary Optimization Using Graph Based Evolutionary Algorithms, proceedings of IMECE, 2003.
  193. Peter E. Johnson, Kenneth M. Bryden, Daniel A. Ashlock, Inverse Solution of a Heat Conduction Problem Using Evolutionary Data Segregation Techniques, proceedings of IMECE, 2003.
  194. Kris Bryden, Kevin Meinert, Dan Ashlock and Kenneth Bryden, Transforming Data into Music Using Fractal Algorithms, in Intelligent Engineering Systems Through Artificial Neural Networks: 665-670, 2002.
  195. Steve Kirstukas, Kenneth Bryden and Daniel A. Ashlock, Evolving Solutions of Differential Equations Utilizing Analytical Derivatives, in Intelligent Engineering Systems Through Artificial Neural Networks:275-280, 2002.
  196. Dan Ashlock, Kenneth Bryden, Peter Johnson and Douglas McCorkle, Improving Data Segregation with a Graph Based Evolutionary Algorithm, in Intelligent Engineering Systems Through Artificial Neural Networks:417-422, 2002.
  197. Dan Ashlock, Andrew Wittrock, and Tsui-Jung Wen, Training Finite State Classifiers to Improve PCR Primer Design, in Proceedings of the 2002 Congress on Evolutionary Computation:13-18, 2002.
  198. Dan Ashlock, Ling Guo, and Fang Qiu, Greedy Closure Genetic Algorithms,in Proceedings of the 2002 Congress on Evolutionary Computation:1296-1301, 2002.
  199. P. Johnson, M. Bryden, D. Ashlock, and E. Vasquez, Evolving Cooperative Partial Functions for Data Summary and Interpolation, in Intelligent Engineering Systems through Artificial Neural Networks:405-410, 2001.
  200. Daniel Ashlock and Jennifer Freeman, A Pure Finite State Baseline for Tartarus, in Proceedings of the 2000 Congress on Evolutionary Computation:1223-1230, 2000.
  201. Daniel Ashlock and James B. Golden III, Iterated Function Systems Fractals for the Detection and Display of DNA Reading Frame, in Proceedings of the 2000 Congress on Evolutionary Computation:1160-1167, 2000.
  202. Daniel Ashlock, Data Crawlers for Optical Character Recognition, in Proceedings of the 2000 Congress on Evolutionary Computation:706-713, 2000.
  203. 21. Kenneth Bryden, Carolina Cruz-Neira, Jeff Doran, Daniel Ashlock, and Shaohau Liu, Interactive Design of Fluid Systems in a Virtual Environment, in Proceedings of the 4th International Immersive Projection Technology Workshop, Ames Iowa, June 19-20:CD- ROM, 2000.
  204. J. L Davidson, R. Thompson, and D. Ashlock, Protein Structure Matching by Genetic Algorithm, in Proceedings of the 2000 International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences, Las Vegas:225-231, 2000.
  205. Daniel Ashlock and Jennifer L. Davidson, Texture Synthesis with Tandem Genetic Algorithms using Nonparametric Partially Ordered Markov Models, om Proceedings of the 1999 Congress on Evolutionary Computation:1157-1163, 1999.
  206. Daniel Ashlock, Mark Smucker, and John Walker, Graph Based Genetic Algorithms, in Proceedings of the 1999 Congress on Evolutionary Computation:1362-1368, 1999.
  207. Daniel Ashlock and John Mayfield, Acquisition of General Adaptive Features by Evolution in EP VII, Proceedings of the Seventh Annual Conference on Evolutionary Programming:75-84, 1998.
  208. Daniel Ashlock and James Lathrop, A Fully Characterized Test Suite for Genetic Programming, in EP VII, Proceedings of the Seventh Annual Conference on Evolutionary Programming:537-546, 1998.
  209. C. Richter, G. Sheble, and D. Ashlock, Effects of Tree Size and State Number on GP-Automata Bidding Strategies, in Genetic Programming 1998, Proceedings of the Second Annual Conference on Genetic Programming:329-337, 1998.
  210. D. Ashlock and M. Joenks, ISAc Lists: A Different Program Induction Method, in Genetic Programming 1998, Proceedings of the Second Annual Conference on Genetic Programming:18-26, 1998.
  211. D. Ashlock and J. Davidson, Lexicodes in the Space of Foot Patterns for Image Classification, in Proceedings of the 1998 IEEE Southwest Symposium on Image Analysis and Interpretation, Tucson, AZ: 97-102, 1998.
  212. Daniel Ashlock, GP-Automata for Dividing the Dollar, in Genetic Programming 1997, Proceedings of the Second Annual Conference on Genetic Programming:18-26, 1997.
  213. Charles Richter and Daniel Ashlock, The Effect of Splitting Populations on Bidding Strategies, in Genetic Programming 1997, Proceedings of the Second Annual Conference on Genetic Programming:27-34, 1997.
  214. D. Ashlock, D. Zheng, and J. L. Davidson, Genetic Algorithms for Automatic Texture Classification, om Statistical and Stochastic Methods in Image Processing II, (F. Preteux, C. Cougherty, J. Davidson, eds.), Proceedings of SPIE, Vol. 3167:140-151, 1997.
  215. Daniel Ashlock, John Walker, and James Oliver, Evolution of Ultrasimple Virtual Robots, Proceedings of the 1996 IEEE International Joint Symposia on Intelligence and Systems.
  216. Xia Hau, Jennifer Davidson, and Daniel Ashlock, A comparison of genetic algorithm, regression, and Newton's method for parameter estimation of texture models, Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, San Antonio, TX:201-206, 1996.
  217. C. Engbretson, J. L. Davidson, and D. Ashlock, Genetic Algorithms for Texture Model Identification and Synthesis, in Statistical and Stochastic Methods in Image Processing, (E. Dougherty, F. Preteux, J. Davidson, eds.), Proceedings of SPIE 2823:20-31, 1996.
  218. Jennifer Davidson, Xia Hau, and Daniel Ashlock, Texture Analysis Using Genetic Algorithms and Partially Ordered Markov Models, in the Proceedings of the International Society for Optical Engineering (SPIE) Conference on Neural, Morphological, and Stochastic Methods in Image and Signal, 2568:197-208, 1995.
  219. E. A. Stanley, Daniel Ashlock, and Mark Smucker, Iterated Prisoner's Dilemma with Choice and Refusal of Partners: Evolutionary Results, om Advances in Artificial Life : Third European Conference on Artificial Life:1995.
  220. D. Ashlock, E. A. Stanley, L. Tesfatsion, Iterated Prisoner's Dilemma with Choice and Refusal, in Alife III, ed. Christopher Langton:131-176, 1994.

Books and Book Chapters

  1. D. Ashlock, C. McGuinness and W. Ashlock, Representation in Evolutionary Computation Chapter in Invited Speakers Book for the 2012 Congress on Evolutionary Computation.
  2. D. Ashlock, Optimization and Modeling with Evolutionary Computation, Springer-Verlag, 2006. This text is an undergraduate introduction to evolutionary computation.
  3. D. Ashlock, Application of Evolutionary Computation to Bioinformatics, Chapter 2 in Genome Exploitation: Data Mining the Genome, J. Perry, R. Shoemaker, J. W. Snape eds, PP 13-30, Springer, 2005.
  4. D. Ashlock and J. W. Goldin III, Evolutionary Computation and Fractal Visualization of Sequence Data, Chapter 11, in Evolutionary Computation in Bioinformatics, Gary B. Fogel and David W. Corne eds., Morgan Kauffman, 2002. Invited Publication.
  5. J.A. Dickerson, D. Berleant, Z. Cox, W. Qi, D. Ashlock, E.S. Wurtele, and A.W. Fulmer, Creating and Modeling Metabolic and Regulatory Networks Using Text Mining and Fuzzy Expert Systems, in Computational Biology and Genome Informatics, edited by Jason T. L. Wang, Cathy H. Wu, Paul Wang, World Scientific Publishing:Singapore:207-238, 2003. Invited Publication
  6. D. Ashlock, Finding Designs with Genetic Algorithms, Chapter 4 in Computational and Constructive Design Theory, edited by Wal Wallis:1996. Invited Publication

Funding

Principal Investigator

  1. Vector Space Techniques for Gene Sequence Analysis, Pioneer Hi-Bred International, $40,000,(01/01/99-12/31/01).
  2. Extraction of Gene Regulation Patterns From Expression Data, Pioneer Hi-Bred International, $11,264.00, (8/23/99-6/30/00).
  3. Visualization of Gene Expression Data, Pioneer Hi-Bred International, $20,000,(01/01/00-12/31/00).
  4. Bioinformatics Tools for Extraction and Modeling of Signal Transduction Networks, Proctor and Gamble Corporation, $220,000, (9/15/00-12/31/02).
  5. An Integrate Database for Barley Genomics, United States Department of Agriculture, $50,000 (8/15/02-8/14/03).
  6. Family Math Night, NSF, $21,802 (9/1/99-6/30/03).
  7. Bioinformatics and Representation, NSERC, $63,000 (9/1/05-8/31/07).
  8. Adaptive computation for Biological Modeling, NSERC, $113,450 (8/31/08-8/31/12).
  9. Developing and Integrated Course in Mathematics and the Physical Sciences, Guelph Learning Enhancement Fund, $100,000 (6/1/09-6/1/10).
  10. Automatic Design, Evolutionary Computation, Computational Intelligence, Product Design, Self-inking stamps, Inteligence Augmentation, NSERC Engage grant with TCI Stamps, $22,869, (6/1/11-3/31/12).
  11. Adaptive Planning for Smart Manufacturing, NSERC Engage grant with Polycon Corporation, $19,339, (1/1/12-9/31/12).
  12. Develop a Software Platform using a Smartphone Interface and a Cloud-Based Application to Enable Consumers to Design Personalized or Monogrammed Merchandise via an In-Store Kiosk, FedDev Grant with InStamp Corporation, $48,000(6/1/12-3/10/13).

Co-principal Investigator

  1. Comparison of Methods for Verification of Energy Improvements, Iowa Energy Center, $120,000 (6/1/98-5/30/01), PI is Ron Nelson of the ISU Mechanical Engineering Department. Renewed for an additional year, amount includes renewal.
  2. Investigation of Interactive Design of Fluids and Heat Transfer Systems within a Virtual Environment, IPRT Research Seed-Funding Program, $126,421.00 (7/1/98-6/30/00) , PI is Mark Bryden of the ISU Mechanical Engineering Department. There is one other co-PI.
  3. An Integrated Field Stream Bioinformatics Data System , National Institutes of Health, $169,540, (08/15/99-05/15/01), PI is Michael K. Bergman of Visualmetrics Corporation. There are four other co-PIs.
  4. High-Throughput Mapping Tools for Maize Genomics , National Science Foundation $2,947,701, (09/01/99-08/31/02), PI is Patrick Schnable of the Iowa State Agronomy Department. There are five other co-PIs.
  5. Computational Analysis for Combining Genomic (EST) Sequences and Expression Profiles, Pioneer Hi-Bred International, $20,000, (01/01/00-12/31/00), PI is Xun Gu of the Iowa State Zoology and Genetic Department.
  6. Algorithms for Resource Allocation under Dynamic Constraints, Rockwell Collins, $159,797.13, (05/01/00-06/01/01), PI is Eric Bartlett of the Electrical and Computer Engineering Department.
  7. Content Preserving Data Synthesis to Support Rapid Design CyclesJohn Deere Corporation, $45,000 (1/1/03-12/31/04), PI is Kenneth Mark Bryden of the Mechanical Engineering Department.
  8. Statistical, Computational, and Genetic Analysis of HIV NIH, $979,194(7/1/03-6/30/07), PI is Karin Dorman of the ISU Statistics department.
  9. VCA - A High-Density Genetic Map of Maize Transcripts, NSF, $3,255,928 (10/1/03-9/30/06), PI is Patrick Schnable of the ISU Agronomy Deprtment.

Students

Doctoral Students

Master's Students

Selected Invited Lectures

  1. An Introduction to Genetic Algorithms, ISU EE General Seminar, Fall 1991.
  2. Artificial Life for Mathematics, ISU Graduate Student Colloquium, Fall 1992.
  3. Complexity Issues in Genetic Algorithms, ISU Computer Science Department Complexity Theory Seminar, Fall 1992.
  4. Theory of Genetic Algorithms, ISU EE General Seminar, October 1992.
  5. Ashlock's Tales, Math Horror Stories, Math Joys, and Interesting Math Objects, Clinton Community College, Spring 1993. (Funded)
  6. Iterated Prisoner's Dilemma with Choice and Refusal, Los Alamos National Laboratories, Summer 1993. (Funded)
  7. Iterated Prisoner's Dilemma with Choice and Refusal, Santa Fe Institute, Santa Fe, New Mexico, Summer 1993. (Funded)
  8. Simulated Annealing, Genetic Algorithms, and Artificial Life Student Chapter, IEEE computer section, Fall 1993.
  9. GP-Automata for Process Control, ISU Power Systems Colloquium, Spring 1996.
  10. One Technique for Finding Rules in Data, ISU Computer Science Colloquium, Fall 1997.
  11. An Introduction to Genetic Algorithms and Data Mining, Proctor and Gamble Corporation, Dec 15-16, 1997. (Funded)
  12. Greedy Genetic Algorithms, ISU Signal Processing Seminar, Spring 1998.
  13. Hybridizing Virtual Robots, ISU Graduate Student Colloquium, Fall 1998.
  14. Rule Induction from Data, ISU IMSE Departmental Colloquium, Fall 1998.
  15. Vector Space Techniques for Gene Sequence Comparison, Pioneer HiBred Corporation, Spring 1999.
  16. Data Visualization, Analysis, and Adaptive Computation., Metabolic Networking in Plants Symposium, hosted by the ISU Botany Dept, Summer 1999.
  17. Short Course on Genetic Algorithms and Related Technologies., Proctor and Gamble Corporation, July 13-16, 1999. (Funded)
  18. What is Bioinformatics, to the Biostatistics Colloquium at the University of Iowa, Spring 2000. (Funded)
  19. Rectophytes, a computational investigation of abstract biological phenomena, Bioinformatics and Computational Biology Student Seminar Series, Iowa State, Sept. 8th 2000.
  20. Am I doing Bioinformatics?, Joint Iowa/Iowa State Workshop on Bioinformatics, Iowa City, Iowa, Nov 3-4, 2000.
  21. Gene Expression Chips: Too Much Data, Botany Club, Iowa State, Nov. 24th, 2000.
  22. Edit Metric Lexicodes for Embedded Genetic Markers, Iowa State Mathematics Colloquium, Nov. 21st, 2000.
  23. Error Correcting Codes in DNA Brock University Computer Science Colloquium, January 14th. 2005. (Funded)
  24. Tartarus ExplorationsKent State University, Computer Science Colloqium, April 26th, 2006. (Funded)
  25. Multiclustering: Avoiding the Underlying MetricCanadian Statistical Society Meetings, May 27, 2006. (Funded)
  26. Multiclustering: Definition and Applications, IEEE Workshop on Multimedia, Mining, and Knowledge Discovery, University of Waterloo, October 18, 2007.
  27. The Impact of Representation on the Evolutionary Prisoner's Dilemma, Keynote Lecture, IEEE Symposium on the Foundations of Computational Intelligence, April 3rd, 2007. (Funded)
  28. Side Effect Machines for Sequence classification National Institute of Mathematical Sciences, DeJong, Korea, June 28, 2008. (Funded).
  29. Evolutionary Computation, Ordinary and Graphical, National Institute of Mathematical Sciences, DeJong, Korea, June 29, 2008. (Funded)

Contributed Talks

  1. Enumerating Permutation Polynomials (mod n) 20th Southeastern International Conference on Combinatorics, Graph Theory and Computing, February, 1989.
  2. A Family of Maximal Star-Free k-Hypergraphs 21st Southeastern International Conference on Combinatorics, Graph Theory and Computing, February, 1990.
  3. The Costas Invariant for Graphs 23rd Southeastern International Conference on Combinatorics, Graph Theory and Computing, February 1992.
  4. Sunburn: Exploration of a Model with a Simple Genetic Algorithm First Symposium on Mathematical Modeling in the Undergraduate Curriculum, June 1993.
  5. Minimal Superpermutations 24th Southeastern International Conference on Combinatorics, Graph Theory and Computing, February 1993.
  6. Prisoner's Dilemma with Choice and Refusal, Third Conference on Artificial Life, July 1993.
  7. Equidimensional Gray Codes in Cayley Graphs, 25th Southeastern International Conference on Combinatorics, Graph Theory and Computing, March 1994.
  8. Edge Separating Maps on Graphs 9th Midwestern Conference on Combinatorics Cryptography and Computing, October 1994.
  9. Matrix Permutation Polynomials over the Integers (mod n) 26th Southeastern International Conference on Combinatorics, Graph Theory and Computing, March 1994.
  10. Virtual Robotics: Undergraduate Projects Second Symposium on Mathematical Modeling in the Undergraduate Curriculum, June 1995.
  11. GP-Automata For Dividing the Dollar 1997 Genetic Programming Conference, July 1997.
  12. A Fully Characterized Test Suite for Genetic Programming , 1998 Conference on Evolutionary Programming, March 1998.
  13. Mathematical Models with Examples, NCTM 1998 National Meeting, February 1998.
  14. Acquisition of General Adaptive Features by Evolution , 1998 Conference on Evolutionary Programming, March 1998.
  15. ISAc lists: a Different Program Induction Technique 1998 Genetic Programming Conference, July 1998.
  16. Texture Synthesis with Tandem Genetic Algorithms using Nonparametric Partially Ordered Markov Models, 1999 Congress on Evolutionary Computation, July 1999.
  17. Graph Based Genetic Algorithms 1999 Congress on Evolutionary Computation, July 1999.
  18. A Pure Finite State Baseline for Tartarus, 2000 Congress on Evolutionary Computation, July 16-19, San Diego Ca.
  19. Iterated Function System Fractals for the Detection and Display of DNA Reading Frame, 2000 Congress on Evolutionary Computation, July 16-19, San Diego Ca.
  20. Training Finite Sate Classifiers to Improve PCR Primer Design, WCCI 2002, May 12-17, Honolulu, Hawaii.
  21. Greedy Closure Genetic Algorithms, WCCI 2002, May 12-17, Honolulu, Hawaii.
  22. Improving Data Segregation with a Graph Based Evolutionary Algorithm, ANNIE 2002, November 10-13 2002, St. Louis, Missouri.
  23. Thermal Agents: Learning Thermal Profiles for Rapid DesignANNIE 2003, St. Louis, Missouri, November 2003.
  24. A Note on General Adaptation in Populations of Painting2003 Congress on Evolutionary Computation, Canberra, Australia, December 2003.
  25. Thermal Agents: An Application of Genetic Programming to Virtual Engineering2003 Congress on Evolutionary Computation, Canberra, Australia, December 2003.
  26. Morphometric Grayscale Texture Analysis using Foot Patterns2003 Congress on Evolutionary Computation, Canberra, Australia, December 2003.
  27. Comparison of Evolved Finite State Classifiers and Interpolated Markov Models for Improving PCR Primer Design, at the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology.
  28. Evolutionary Control of Bracked L-system Interpretation at ANNIE '04, November 2004.
  29. Taxonomy of evolutionary computation problems at ANNIE '04, November 2004.
  30. Evolutionary Control of L-system Interpretation at the 2004 Congress on Evolutionary Computation.
  31. Coevolution and Tartarus at the 2004 Congress on Evolutionary Computation.
  32. Program Induction: Building a Wall, at the 2004 Congress on Evolutionary Computation.

    Service

    Departmental

    Interdisciplinary

    College

    University

    Professional

    Outreach