Numerical simplification for bloat control and analysis of building blocks in genetic programming

Soule T, Foster JA, Dickinson J (1996) Code growth in genetic programming. In: Koza JR et al (eds) Genetic programming 1996: proceedings of the first annual conference. Stanford University, MIT Press, USA, pp 215–223

Soule T, Heckendorn RB (2002) An analysis of the causes of code growth in genetic programming. Genet Program Evolvable Mach 3(3):283–309

Blickle T, Thiele, L (1994) Genetic programming and redundancy. In: Hopf J (ed) Genetic algorithms within the framework of evolutionary computation. Max-Planck-Institut für Informatik (MPI-I-94-241), pp 33–38

Koza JR (1992) Genetic programming: on the programming of computers by means of natural selection. MIT Press, Cambridge

Soule T, Foster JA (1997) Support for multiple causes of code growth in GP. Position paper at the workshop on evolutionary computation with variable size representation at ICGA 1997, July 20

Soule T (1998) Code growth in genetic programming. PhD thesis, University of Idaho, Moscow, Idaho, USA, May 15

Banzhaf W, Nordin P, Keller RE, Francone FD (1998) Genetic programming: an introduction on the automatic evolution of computer programs and its applications. Morgan Kaufmann Publishers Inc., San Francisco

Zhang M, Smart W (2006) Using gaussian distribution to construct fitness functions in genetic programming for multiclass object classification. Pattern Recognit Lett 27(11):1266–1274

Wong P, Zhang M (2006) Algebraic simplification of GP programs during evolution. In: Keijzer M et al (eds) GECCO 2006: proceedings of the 8th annual conference on genetic and evolutionary computation, vol 1. ACM Press, USA, pp 927–934

Nordin P, Banzhaf W (1995) Complexity compression and evolution. In: Eshelman L (ed) Genetic algorithms: proceedings of the sixth international conference (ICGA95). Morgan Kaufmann, Pittsburgh, pp 310–317, 15–19 July

Parrott D, Li X, Ciesielski V (2005) Multi-objective techniques in genetic programming for evolving classifiers. In: Corne D, Michalewicz Z et al (eds) Proceedings of the 2005 IEEE congress on evolutionary computation vol 2. IEEE Press, Edinburgh, pp 1141–1148, 2–5 Sep

Zhang BT, Mühlenbein H (1995) Balancing accuracy and parsimony in genetic programming. Evol Comput 3(1):17–38

Zhang M, Bhowan U (2004) Program size and pixel statistics in genetic programming for object detection. In: Raidl GR, Cagnoni S, et al. (eds) Applications of evolutionary computing, evoworkshops 2004. vol 3005 LNCS, Springer, Coimbra, pp 379–388, 5–7 April

Luke S, Panait L (2002) Lexicographic parsimony pressure In: Langdon WB et al (eds) GECCO 2002: proceedings of the genetic and evolutionary computation conference. Morgan Kaufmann, New York, pp 829–836, 9–13 July

de Jong ED, Pollack JB (2003) Multi-objective methods for tree size control. Genet Program Evolvable Mach 4(3):211–233

Luke S, Panait L (2002) Fighting bloat with nonparametric parsimony pressure. In: Merelo Guervos JJ, Adamidis P, Beyer HG, Fernandez-Villacanas JL, Schwefel HP (eds) Proceedings of the international conference on parallel problem solving from nature (PPSN VII). Springer, The Netherland pp 411–421

Poli R (2003) A simple but theoretically-motivated method to control bloat in genetic programming. In: Genetic programming, proceedings of EuroGP 2003. Springer, The Netherland pp 204–217

Luke S, Panait L (2004) Alternative bloat control methods In: Genetic and evolutionary computation—GECCO-2004, Part II (Lecture Notes in Computer Science). Springer, The Netherland pp 630–641

Blickle T, Thiele L (1994) Genetic programming and redundancy, In: Hopf J (ed) Genetic algorithms within the fram work of evolutionary computation. Workshop at KI-94, Saarbrüken, Im Stadtwald, Building 44, D-66123 Saarbrüken, Germany, Max-Planck-Institut für Informatik, MPI-I-94-241, pp 33–38

Ashlock W, Ashlock D (2005) Single parent genetic programming, In: Corne D, Mickalewicz Z, Dorigo M, Eiben G, Fogel D, Fonseca C, Greenwood G, Chen TK, Raidl G, Zalzala A, Lucas S, Paechter B, Willies J, Guervos JJM, Eberbach E, McKay B, Channon A, Tiwari A, Volkert LG, Asklock D, Schoenauer M (eds) Proceedings 2005 IEEE congress evolutionary computation, vol 2. IEEE Press, Edinburgh, pp 1172–1179, 2–5 September

Langdon WB, Poli R (1997) Fitness causes bloat. In: Chawdhry PK, Roy R, Pant RK (eds) Soft computing in engineering design and manufacturing. Springer, London, 23–27 June, pp 13–22

Nordin P, Francone F, Banzhaf W (1995) Explicitly defined introns and destructive crossover in genetic programming, In: Rosca JP (eds) Proceedings workshop on genetic programming: from theory to real-world applications. Tahoe City, pp 6--22, 9 July

Hooper D, Flann NS (1996) Improving the accuracy and robustness of genetic programming through expression simplification, In: Koza JR et al. (eds) Genetic programming 1996: proceedings of the first annual conference. Stanford University, MIT Press, CA, p 428

Wong P, Zhang M (2007) Effects of program simplification on simple building blocks in genetic programming. In: IEEE congress on evolutionary computation pp 1570–1577

Mori N, Matsumoto K (2005) A novel measure of diversity in genetic programming by means of subtree entropy. In: Proceedings 32nd SICE symposium on intelligent systems, pp 205–210 (in Japanese)

Kang M, Shin J, Hoang TH, McKay B, Essam D, Mori N, Nguyen XH (2006) Code duplication and developmental evaluation in genetic programming. In: Proceedings 2006 asia-pacific workshop on intelligent and evolutionary systems. Seoul, Korea pp 181–191

Marshall D (2001) The discrete cosine transform. http://www.cs.cf.ac.uk/Dave/Multimedia/node231.html

Forina M, Leardi R, Armanino C, Lanteri S (1988) Parvus: an extendable package of programs for data exploration, classification and correlation. Elsevier, Amsterdam

Witten IH, Frank E (2005) Data mining: practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann, San Francisco

Samaria F, Harter AC (1994) Parameterisation of a stochastic model for human face identification. proceedings of the second IEEE workshop on applications of computer vision

Wilcoxon F (1945) Individual comparisons by ranking methods. Biometrics 1:80–83

LaVange LM, Koch Gary G (2006) Rank score tests. Circulation 114(23):2528–2533