Dr. R. Matthew Kretchmar
Research Activities and Publications
My current Curriculum Vitae. (pdf)
Research Interests and Activities
My primary research interests are in machine learning and reinforcement learning in particular. I am interested in function approximation, robust and stable control, neuro-control, combinatorics, multi-agent learning and evolutionary computation. I also dabble in genetic algorithms, neural networks, philosophy of the mind, cognitive psychology, evolutionary biology, game theory, and artificial life.
Publications
Kretchmar, R.M. Exploring Equity in the Golf Skins Game. Midwest Sports Analytics Meeting. Central College: Pella, IA. November 21, 2020.Kretchmar, R.M. Analyzing Equity in High School Cross Country Competition. Midwest Sports Analytics Meeting. Central College: Pella, IA. November 23, 2019.
Kretchmar, R.M. Measuring Equity in High School Cross Country Running. Great Lakes Data Analytics Conference. University of Wisconsin Stevens Point. October 2019.
Kretchmar, M. The Effect of School Size on Cross Country Performance. Preprint, preparing for submission. 2019. (pdf)
Kretchmar, M. Equitable Divisional Alignment for High School Cross Country Competitions. Preprint, preparing for submission. 2019. (pdf)
DeVeaux, Richard, Mahesh Agarwal, Maia Averett, Benjamin S. Baumer, Andrew Bray, Thomas C. Bressoud, Lance Bryant, Lei Z. Cheng, Amanda Francis, Robert Gould, Albert Y. Kim, Matt Kretchmar, Qin Lu, Ann Moskol, Deborah Nolan, Roberto Pelayo, Sean Raleigh, Ricky J. Sethi, Mutiara Sondjaja, Neelesh Tiruviluamala, Paul X. Uhlig, Talitha M. Washington, Curtis L. Wesley, David White, and Ping Ye. Curriculum Guidelines for Undergraduate Programs in Data Science. Annual Review of Statistics and Its Application. v4. pg 15-30. March 2017.
Kretchmar, M. Using Portfolios in Science Classes. Invited talk at Otterbein University. Fall 2016.
Kretchmar, R.M. A Portfolio Based Pedagogy for CS Courses. AACU's Ohio Project Kaleidoscope: STEM Conference for Learning Pedagogies and Underprepared students. June 2016.
Kretchmar, R.M. Integrating Writing into STEM Courses. AACU's Ohio Project Kaleidoscope: STEM Conference for Learning Pedagogies and Underprepared students. June 2016.
R. M. Kretchmar, and Y. Zhao. Text Message Authorship Classification Using Kernel Support Vector Machines. Computational Science and Computational Intelligence, CSCI '14. Las Vegas, NV. March 2014.
N. Kell, and R. M. Kretchmar. Suspense at the Ballot Box. College Mathematics Journal vol 44, no 1, pp 9-16. 2013.
Bucantanschi, D., B. Hoffman, K. Hutson, and R. M. Kretchmar. A Neighborhood Search Technique for the Freeze Tag Problem. Extending the Gap: Advances in Computing, Optimization, and Decision Technologies , E. Baker, A. Joseph, A. Mehrotra, and M. Trick (eds.), Springer, 2007, pp. 97-113.
D. Bucatanschi. Kernel Methods for Image Processing. Denison University Honors Thesis. April 2006. (pdf)
T. Feil, K. Hutson, and R. M. Kretchmar. Tree Traversals and Permutations. Congressus Numerantium. Vol 172, pp.201-221. 2005. (pdf)
Charles W. Anderson, R. Matthew Kretchmar, Peter Young, and Douglas Hittle. Robust Reinforcement Learning Using Integral Quadratic Constraints. Chapter in: Handbook of Learning and Approximate Dynamic Programming. IEEE Press: Piscataway, NJ. 2004.
Charles W. Anderson, Douglas Hittle, R. Matthew Kretchmar, and Peter Young. Robust Reinforcement Learning for Heating, Ventilation, and Air Conditioning Control of Buildings. Chapter in: Handbook of Learning and Approximate Dynamic Programming. IEEE Press: Piscataway, NJ. 2004.
R. M. Kretchmar, T. Feil, and R. Bansal. Improved Automatic Discovery of Subgoals for Options in Hierarchical Reinforcement Learning. Journal of Computer Science and Technology. October, 2003. (pdf)
R. M. Kretchmar. Complex Systems: Searching for the Empirical in CS. The MITC Symposium on Innovative Science Teaching: Enhancing Learning with Technology. Depauw University, Greencastle, IN. May, 2003.
R. M. Kretchmar, and D. Antonova. Machine Learning in a Distributed Agent Environment. The GLCA Conference on Complex Systems. Kalamazoo College, Kalamazoo, MI. February, 2003.
R. M. Kretchmar. Parallel Reinforcement Learning. SCI2002. The 6th World Conference on Systemics, Cybernetics, and Informatics. 2002. (postscript) (pdf)
R. M. Kretchmar, Peter M. Young, C. W. Anderson, Douglas C. Hittle, Michael L. Anderson, Jilin Tu and Christopher C. Delnero. Robust Reinforcement Learning Control. ACC2001: 2001 American Control Conference: Washington DC. June 2001. (postscript)
Kretchmar, R.M., Young, P.M., Anderson, C.W., Hittle, D.C., Anderson, M. L., Delnero, C. C. (2001) Robust Reinforcement Learning Control with Static and Dynamic Stability. International Journal of Robust and Nonlinear Control. no. 11, pp. 1469-1500, 2001. (pdf)
R. M. Kretchmar. A Synthesis of Reinforcement Learning and Robust Control Theory, Ph.D. Dissertation. Colorado State University: Fort Collins, CO. August 2000. (compress, postscript)
R. M. Kretchmar and C. W. Anderson. Using Temporal Neighborhoods to Adapt Function Approximators in Reinforcement Learning. IWANN99: International Work Conference on Artificial and Natural Neural Networks : Alicante, Spain. June 1999. (postscript)
R. M. Kretchmar and C. W. Anderson Comparison of CMACs and Radial Basis Functions for Local Function Approximators in Reinforcement Learning. ICNN'97. International Conference on Neural Networks. 1997. (postscript)
Kretchmar, R. Matthew. Uncontrolling Technology . A review of Kevin Kelly's book, Out of Control . Research in Philosophy and Technology. Vol 16. Ed. Karl Mitcham. 1997.
Anderson, C. W., Hittle, D., Katz, A. and Kretchmar, R. Synthesis of Reinforcement Learning, Neural Networks, and PI Control Applied to a Simulated Heating Coil. Journal of Artificial Intelligence in Engineering , Vol. 11, #4, pp. 423 R 431, 1997. (pdf)
Anderson, C. W., Hittle, D. C., Katz, A. D., and Kretchmar, R. M. Reinforcement Learning, Neural Networks and PI Control Applied to a Heating Coil. Solving Engineering Problems with Neural Networks: Proceedings of the International Conference on Engineering Applications of Neural Networks (EANN'96) . ed. Bulsari, A. B., Kallio, S. and Tsaptsinos, D. Systems Engineering Association, PL 34, FIN-20111 Turku 11, Finland. pp 135-142, 1996. (pdf)