Abstract
Grammar-based genetic programming systems have gained interest in recent decades and are widely used nowadays. Although researchers normally present the grammar used to solve a certain problem, they seldom write about processes used to construct the grammar. This paper sheds some light on how to design a grammar that not only covers the search space, but also supports the search process in finding good solutions. The focus lies on context free grammar guided systems using derivation tree crossover and mutation, in contrast to linearised grammar based systems. Several grammars are presented encompassing the search space of sorting networks and show concepts which apply to general grammar design. An analysis of the search operators on different grammar is undertaken and performance examined on the sorting network problem. The results show that the overall structure for derivation trees created by the grammar has little effect on the performance, but still affects the genetic material changed by search operators.
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Cleary, R., O’Neill, M.: An attribute grammar decoder for the 01 multiconstrained knapsack problem. In: Raidl, G.R., Gottlieb, J. (eds.) EvoCOP 2005. LNCS, vol. 3448, pp. 34–45. Springer, Heidelberg (2005)
Codish, M., Cruz-Filipe, L., Frank, M., Schneider-Kamp, P.: Twenty-five comparators is optimal when sorting nine inputs (and twenty-nine for ten). CoRR (2014)
Daida, J., Hilss, A.: Identifying structural mechanisms in standard genetic programming. In: Cantú-Paz, E., et al. (eds.) Genetic and Evolutionary Computation — GECCO 2003. LNCS, vol. 2724, pp. 1639–1651. Springer, Heidelberg (2003)
Dempsey, I., O’Neill, M., Brabazon, A.: Constant creation in grammatical evolution. Int. J. Innovative Comput. Appl. 1, 23–38 (2007)
Dempsey, I., O’Neill, M., Brabazon, A.: Grammatical evolution. In: Dempsey, I., O’Neill, M., Brabazon, A. (eds.) Foundations in Grammatical Evolution for Dynamic Environments. SCI, vol. 194, pp. 9–24. Springer, Heidelberg (2009)
Hemberg, E.: University College, D.S.o.C.S.I. An exploration of grammars in grammatical evolution. Ph.D. thesis, University College Dublin, Ireland (2010)
Hoai, N.X., McKay, R., Essam, D.: Representation and structural difficulty in genetic programming. IEEE Trans. Evol. Comput. 10(2), 157–166 (2006)
Keijzer, M., Babovic, V., Ryan, C., O’Neill, M., Cattolico, M.: Adaptive logic programming. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001), California, USA, pp. 42–49, 7–11 July 2001
Knuth, D.E.: The Art of Computer Programming. Sorting and Searching, vol. 3, 2nd edn. Addison Wesley Longman Publishing Co. Inc, Redwood City (1998)
Koza, J.R., Andre, D., Bennett, F.H., Keane, M.A.: Genetic Programming III: Darwinian Invention & Problem Solving, 1st edn. Morgan Kaufmann Publishers Inc., San Francisco (1999)
Koza, J.R., Bennett I, F.H., Hutchings, J., Bade, S., Keane, M.A., Andre, D.: Evolving sorting networks using genetic programming and the rapidly reconfigurable xilinx 6216 field-programmable gate array. In: Conference Record of the Thirty-First Asilomar Conference on Signals, Systems amp; Computers, vol. 1, pp. 404–410, November 1997
Luke, S.: Two fast tree-creation algorithms for genetic programming. IEEE Trans. Evol. Comput. 4(3), 274–283 (2000)
McDermott, J., Swafford, J.M., Hemberg, M., Byrne, J., Hemberg, E., Fenton, M., McNally, C., Shotton, E., O’Neill, M.: String-rewriting grammars for evolutionary architectural design. Environ. Plann. B Plann. Des. 39(4), 713–731 (2012)
McKay, R., Hoai, N., Whigham, P., Shan, Y., ONeill, M.: Grammar-based genetic programming: a survey. Genet. Program. Evolvable Mach. 11(3–4), 365–396 (2010)
Montana, D.J.: Strongly typed genetic programming. Evol. Comput. 3(2), 199–230 (1995)
Murphy, E., O’Neill, M., Galvapez, E., Brabazon, A. : Tree-adjunct grammatical evolution. In: 2010 IEEE Congress on Evolutionary Computation (CEC), pp. 1–8 (2010)
Murphy, E.: An exploration of tree-adjoining grammars for grammatical evolution. Ph.D. thesis, University College Dublin, Ireland, 6 December 2014
Murphy, E., Hemberg, E., Nicolau, M., O’Neill, M., Brabazon, A.: Grammar bias and initialisation in grammar based genetic programming. In: Moraglio, A., Silva, S., Krawiec, K., Machado, P., Cotta, C. (eds.) EuroGP 2012. LNCS, vol. 7244, pp. 85–96. Springer, Heidelberg (2012)
Nicolau, M.: Automatic grammar complexity reduction in grammatical evolution. In: GECCO 2004 Workshop Proceedings, Seattle, Washington, USA (2004)
O’Neill, M., Nicolau, M., Agapitos, A.: Experiments in program synthesis with grammatical evolution: A focus on integer sorting. In: 2014 IEEE Congress on Evolutionary Computation (CEC), pp. 1504–1511, July 2014
O’Neill, M., McDermott, J., Swafford, J.M., Byrne, J., Hemberg, E., Brabazon, A., Shotton, E., McNally, C., Hemberg, M.: Evolutionary design using grammatical evolution and shape grammars: designing a shelter. Int. J. Des. Eng. 3(1), 4–24 (2010)
O’Neill, M., Ryan, C.: Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language. Kluwer Academic Publishers, Berlin (2003)
Ryan, C., Nicolau, M., O’Neill, M.: Genetic algorithms using grammatical evolution. In: Foster, J.A., Lutton, E., Miller, J., Ryan, C., Tettamanzi, A.G.B. (eds.) EuroGP 2002. LNCS, vol. 2278, pp. 278–287. Springer, Heidelberg (2002)
Sekanina, L., Bidlo, M.: Evolutionary design of arbitrarily large sorting networks using development. Genet. Program. Evolvable Mach. 6(3), 319–347 (2005)
Tanev, I.: Incorporating learning probabilistic context-sensitive grammar in genetic programming for efficient evolution and adaptation of snakebot. In: Keijzer, M., Tettamanzi, A.G.B., Collet, P., van Hemert, J., Tomassini, M. (eds.) EuroGP 2005. LNCS, vol. 3447, pp. 155–166. Springer, Heidelberg (2005)
Wagner, S., et al.: Architecture and design of the heuristiclab optimization environment. In: Klempous, R., Nikodem, J., Jacak, W., Chaczko, Z. (eds.) Advanced Methods and Applications in Computational Intelligence. TIEI, vol. 6, pp. 193–258. Springer, Heidelberg (2013)
Whigham, P.A.: Grammatical bias for evolutionary learning. Ph.D. thesis, New South Wales, Australia, Australia (1996)
Wong, M.L., Leung, K.S.: Evolutionary program induction directed by logic grammars. Evol. Comput. 5(2), 143–180 (1997)
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This research is based upon works supported by the Science Foundation Ireland, under Grant No. 13/IA/1850.
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Forstenlechner, S., Nicolau, M., Fagan, D., O’Neill, M. (2016). Grammar Design for Derivation Tree Based Genetic Programming Systems. In: Heywood, M., McDermott, J., Castelli, M., Costa, E., Sim, K. (eds) Genetic Programming. EuroGP 2016. Lecture Notes in Computer Science(), vol 9594. Springer, Cham. https://doi.org/10.1007/978-3-319-30668-1_13
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