Abstract
This paper assesses the new numerical-constant generation method called ephemeral constant, which can be seen as a translation of the classical genetic programming’s ephemeral random constant to the grammatical evolution framework. Its most distinctive feature is that it decouples the number of bits used to encode the grammar’s production rules from the number of bits used to represent a constant. This makes it possible to increase the method’s representational power without incurring in an overly redundant encoding scheme. We present experiments comparing ephemeral constant with the three most popular approaches for constant handling: the traditional approach, digit concatenation, and persistent random constant. By varying the number of bits to represent a constant, we can increase the numerical precision to the desired level of accuracy, overcoming by a large margin the other approaches.
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References
Augusto, D.A., Barreto, A.M., Barbosa, H.J., Bernardino, H.S.: A new approach for generating numerical constants in grammatical evolution. In: Proc. of the Conf. on Genetic and Evolutionary Computation (2011) Extended Abstract
Bernardino, H.S., Barbosa, H.J.: Grammar-Based Immune Programming for Symbolic Regression. In: Andrews, P.S., Timmis, J., Owens, N.D.L., Aickelin, U., Hart, E., Hone, A., Tyrrell, A.M. (eds.) ICARIS 2009. LNCS, vol. 5666, pp. 274–287. Springer, Heidelberg (2009)
Bernardino, H.S., Barbosa, H.J.: Grammar-based immune programming. Natural Computing, 1–33 (2010)
Cramer, N.L.: A representation for the adaptive generation of simple sequential programs. In: Proc. 1st Intl. Conf. on Genetic Algorithms, Hillsdale, NJ, USA, pp. 183–187 (1985)
Dempsey, I., O’Neill, M., Brabazon, A.: Grammatical constant creation. In: Proc. Conf. on Genetic and Evolutionary Computation, pp. 447–458 (2004)
Dempsey, I., O’Neill, M., Brabazon, A.: Meta-grammar constant creation with grammatical evolution by grammatical evolution. In: Proc. Conf. on Genetic and Evolutionary Computation, pp. 1665–1671. ACM, New York (2005)
Dempsey, I., O’Neill, M., Brabazon, A.: Constant creation in grammatical evolution. Int. J. Innov. Comput. Appl. 1, 23–38 (2007)
Dolan, E., Moré, J.J.: Benchmarking optimization software with performance profiles. Math. Programming 91(2), 201–213 (2002)
Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)
O’Neill, M., Brabazon, A.: Grammatical differential evolution. In: Proc. Intl. Conf. on Artificial Intelligence, Las Vegas, NV, USA, pp. 231–236 (2006)
O’Neill, M., Brabazon, A., Adley, C.: The automatic generation of programs for classification problems with grammatical swarm. In: Proc. of the Congress on Evolutionary Computation, vol. 1, pp. 104–110 (2004)
O’Neill, M., Dempsey, I., Brabazon, A., Ryan, C.: Analysis of a Digit Concatenation Approach to Constant Creation. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E.P.K., Poli, R., Costa, E. (eds.) EuroGP 2003. LNCS, vol. 2610, pp. 173–182. Springer, Heidelberg (2003)
O’Neill, M., Ryan, C.: Grammatical evolution. IEEE Trans. Evol. Comput. 5(4), 349–358 (2001)
O’Neill, M., Ryan, C.: Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language. Kluwer Academic Publishers (2003)
Rowe, J., Whitley, D., Barbulescu, L., Watson, J.-P.: Properties of gray and binary representations. Evol. Comput. 12, 47–76 (2004)
Ryan, C., Collins, J.J., Neill, M.O.: Grammatical Evolution: Evolving Programs for an Arbitrary Language. In: Banzhaf, W., Poli, R., Schoenauer, M., Fogarty, T.C. (eds.) EuroGP 1998. LNCS, vol. 1391, pp. 83–95. Springer, Heidelberg (1998)
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Augusto, D.A., Barbosa, H.J.C., Barreto, A.M.S., Bernardino, H.S. (2011). Evolving Numerical Constants in Grammatical Evolution with the Ephemeral Constant Method. In: Antunes, L., Pinto, H.S. (eds) Progress in Artificial Intelligence. EPIA 2011. Lecture Notes in Computer Science(), vol 7026. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24769-9_9
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DOI: https://doi.org/10.1007/978-3-642-24769-9_9
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