Abstract
This chapter describes how genetic programming might be integrated as a tool into the human context of discovery. To accomplish this, a comparison is made between GP and a well-regarded strategy in open-ended problem solving. The comparison indicates which tasks and skills are likely to be complemented by GP. Furthermore, the comparison also indicates directions in research that may need to be taken for GP to be further leveraged as a tool that assists discovery.
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References
Caplan, M. and Y. Beker (2004). Lessons Learned Using Genetic Programming in a Stock Picking Context: A Story of Willful Optimism and Eventual Success. Genetic Programming Theory and Practice II. U.-M. O’Reilly, T. Yu, R. L. Riolo and W. Worzel. Boston, Kluwer Academic Publishers: 31–48.
Castillo, F., A. Kordon, et al. (2004). Using Genetic Programming in Industrial Statistical Model Building. Genetic Programming Theory and Practice II. U.-M. O’Reilly, T. Yu, R. L. Riolo, and W. Worzel. Boston, Kluwer Academic Publishers: 31–48.
Daida, J. M. (2004). What Makes a Problem GP-Hard? A Look at How Structure Affects Content. Genetic Programming Theory and Practice. R. L. Riolo and W. Worzel. New York, Springer: 99–118.
Daida, J. M. (2005). Considering the Roles of Structure in Problem-Solving by Computer. Genetic Programming Theory and Practice II. U.-M. O’Reilly, T. Yu, R. L. Riolo and W. Worzel. New York, Springer: 67–86.
Daida, J. M. (2005). Towards Identifying Populations that Increase the Likelihood of Success in Genetic Programming. GECCO 2005. In print.
Daida, J. M., A. M. Hilss, et al. (2005). “Visualizing Tree Structures in Genetic Programming.” Genetic Programming and Evolvable Machines 6: 79–110.
Goldberg, D. (2002). The Design of Innovation: Lessons from and for Competent Genetic Algorithms. Boston, Kluwer Academic Publishers.
Keane, M. A., J. R. Koza, et al. (2002). General-Purpose Controllers. Patent #6,847,851. Issued 25 January 2005. U. S. Patent Office. United States. Assignee: Koza, J.R.
Koza, J. R. (1992). Genetic Programming: On the Programming of Computers by Means of Natural Selection. Cambridge, The MIT Press.
Koza, J. R., F. H. Bennett III, et al. (1999). Genetic Programming III Darwinian Invention and Problem Solving. San Francisco, Morgan Kaufmann Publishers.
Koza, J. R., L. W. Jones, et al. (2004). Toward Automated Design of Industrial-Strength Analog Circuits by Means of Genetic Programming. Genetic Programming Theory and Practice II. U.-M. O’Reilly, T. Yu, R. L. Riolo, and W. Worzel. Boston, Kluwer Academic Publishers: 121–142.
Koza, J. R., M. A. Keane, et al. (2003). Genetic Programming IV: Routine Human-Competitive Machine Intelligence. Norwell, Kluwer Academic Publishers.
Koza, J. R., M. A. Keane, et al. (2000). “Automatic Creation of Human-Competitive Programs and Controllers by Means of Genetic Programming.” Genetic Programming and Evolvable Machines 1(1/2): 121–164.
Lipson, H. and J. B. Pollack (2000). “Automatic Design and Manufacture of Robotic Lifeforms.” Nature 406 (31 August 2000): 974–978.
Lohn, J. D., G. S. Hornby, et al. (2004). An Evolved Antenna for Deployment on NASA’s Space Technology 5 Mission. Genetic Programming Theory and Practice II. U.-M. O’Reilly, T. Yu, R. L. Riolo, and W. Worzel. Boston, Kluwer Academic Publishers: 301–313.
MacLean, D., E. A. Wollesen, et al. (2004). Listening to Data: Tuning a Genetic Programming System. Genetic Programming Theory and Practice II. U.-M. O’Reilly, T. Yu, R. L. Riolo, and W. Worzel. Boston, Kluwer Academic Publishers: 245–262.
Michalewicz, Z. and D. B. Fogel (2000). How to Solve It: Modern Heuristics. Berlin, Springer-Verlag.
Orbach, R. L. (2002). Testimony of Dr. Raymond L. Orbach, Director, Office of Science, Before the House Science Committee Subcommittee on Energy. Washington, D.C.
Poundstone, W. (2003). How Would You Move Mount Fuji? Microsoft’s Cult of the Puzzle: How the World’s Smartest Companies Select the Most Creative Thinkers. Boston, Little, Brown and Company.
Root-Bernstein, R. S. (1989). Discovering: Inventing and Solving Problems at the Frontiers of Scientific Knowledge. Cambridge, Harvard University Press.
Triendl, R. (2002). “Our Virtual Planet.” Nature 416 (11 April 2002): 579–580.
Woods, D. R. (1994). Problem-Based Learning: How to Gain the Most from PBL. Waterdown, ON, Woods Publishing.
Woods, D. R. (2000). “An Evidence-Based Strategy for Problem Solving.” Journal of Engineering Education: 443–459.
Woods, D. R., A. Hrymak, et al. (1997). “Developing Problem Solving Skills: The McMaster Problem Solving Program.” Journal of Engineering Education: 75–91.
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Daida, J.M. (2006). Challenges in Open-Ended Problem Solving with Genetic Programming. In: Yu, T., Riolo, R., Worzel, B. (eds) Genetic Programming Theory and Practice III. Genetic Programming, vol 9. Springer, Boston, MA. https://doi.org/10.1007/0-387-28111-8_17
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DOI: https://doi.org/10.1007/0-387-28111-8_17
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