Abstract
Welcome to genetic programming, where the forces of nature are used to automatically evolve computer programs. We give a flavour of where GP has been successfully applied (it is far too wide an area to cover everything) and interesting current and future research but start with a tutorial of how to get started and finish with common pitfalls to avoid.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Notes
- 1.
Darwin was the naturalist onboard HMS Beagle for 5 years [6].
- 2.
A word of caution: GP and grammar terminology were both developed before grammar-based GP systems and use some of the same words. Unfortunately, when they came together in grammar-based GP, some inconsistencies arose. Thus, in a CFG-GP system, a (GP) function symbol is a terminal (in grammar terms), though it is not a member of the GP terminal set. Unfortunately there does not seem to be any reasonable way to resolve this inconsistency.
References
Turing, A.M.: Intelligent machinery. Report for National Physical Laboratory. Reprinted in Ince, D.C. (ed.) (1992) Mechanical Intelligence: Collected Works of A.M. Turing. (1948)
Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press (1992)
Darwin, C.: The Origin of Species, 1985 edn. John Murray, Penguin classics (1859)
Banzhaf, W., Nordin, P., Keller, R.E., Francone, F.D.: Genetisc Programming– An Introduction; On the Automatic Evolution of Computer Programs and its Applications. Morgan Kaufmann, San Francisco, CA, USA (1998)
Poli, R., Langdon, W.B., McPhee, N.F.: A field guide to genetic programming. Published via http://lulu.com and freely available at http://www.gp-field-guide.org.uk, (2008) (With contributions by Koza, J.R.)
Darwin, C.: Voyage of the Beagle. Henry Colburn, London, penguin classics, 1989 edition, (1839)
Nordin, P., Banzhaf, W., Francone, F.D.: Efficient evolution of machine code for CISC architectures using instruction blocks and homologous crossover. In: Spector, L., Langdon, W.B., O’Reilly, U.-M., Angeline, P.J. (eds.) Advances in Genetic Programming 3, chapter 12, pp. 275–299. MIT Press, Cambridge, MA, USA (1999)
Foster, J.A.: Review: Discipulus: a commercial genetic programming system. GP&EM, 2(2), 201–203 (2001)
Brameier, M., Banzhaf, W.: A comparison of linear genetic programming and neural networks in medical data mining. IEEE Trans. EC, 5(1), 17–26 (2001)
Poli, R.: Discovery of symbolic, neuro-symbolic and neural networks with parallel distributed genetic programming. Technical Report CSRP-96-14, University of Birmingham, School of Computer Science, August 1996. Presented at 3rd International Conference on Artificial Neural Networks and Genetic Algorithms, ICANNGA’97
Teller, A.: Evolving programmers: The co-evolution of intelligent recombination operators. In: Angeline, P.J., Kinnear, Jr., K.E. (eds.) Advances in Genetic Programming 2, chapter 3, pp. 45–68. MIT Press, Cambridge, MA, USA (1996)
Miller, J.F., Smith, S.L.: Redundancy and computational efficiency in cartesian genetic programming. IEEE Trans. EC, 10(2), 167–174 (2006)
Langdon, W.B.: Size fair and homologous tree genetic programming crossovers. GP&EM, 1(1/2), 95–119 (2000)
Goldberg, D.E.: Genetic Algorithms in Search Optimization and Machine Learning. Addison-Wesley, (1989)
Angeline, P.J.: Subtree crossover: building block engine or macromutation? In: Koza et al., J.R. (eds.) GP 1997, pp. 9–17. Morgan Kaufmann, Stanford, 13–16 Jul.
Braitenberg, V.: Vehicles. MIT Press, (1984)
Poli, R., Page, J., Langdon, W.B.: Smooth uniform crossover, sub-machine code GP and demes: A recipe for solving high-order boolean parity problems. In: Banzhaf, W., Daida, J., Eiben, A.E., Garzon, M.H., Honavar, V., Jakiela, M., Smith, R.E. (eds.) Proceedings of the Genetic and Evolutionary ComputationConference, volume 2, pp. 1162–1169. Morgan Kaufmann, Orlando, Florida, USA (1999)
Chomsky, N.: Three models for the description of language. IEEE Trans. Inf. Theory, 2(3), 113–124 (1956)
Montana, D.J.: Strongly typed genetic programming. Evol. Comput., 3(2), 199–230 (1995)
Recknagel et al., F.: Comparative application of artificial neural networks and genetic algorithms for multivariate time series modelling of algal blooms in freshwater lakes. HydroInformatic, 4(2), 125–134 (2002)
Ratle, A., Sebag, M.: Genetic programming and domain knowledge: Beyond the limitations of grammar-guided machine discovery. In: Schoenauer, M., Deb, K., Rudolph, G., Yao, X., Lutton, E., JulianMerelo, J., Schwefel, H.-P. (eds.) Parallel Problem Solving from Nature – PPSN VI 6th International Conference, volume 1917 of LNCS, pp. 211–220. Springer Verlag, Paris, France (2000)
Wong, M.L., Leung, K.S.: Inductive logic programming using genetic algorithms. In: Brahan, J.W., Lasker, G.E. (eds.) Advances in Artificial Intelligence - Theory and Application II, pp. 119–124. I.I.A.S., Ontario, Canada (1994)
Hussain, T.S., Browse, R.A.: Attribute grammars for genetic representations of neural networks and syntactic constraints of genetic programming. In Workshop on Evolutionary Computation. Held at the 12 Candadian Conference on Artificial Intelligence, Vancouver, Canada (1998)
Paterson, N.R., Livesey, M.: Distinguishing genotype and phenotype in genetic programming. In: John, R. Koza, (ed.) Late Breaking Papers at the Genetic Programming1996 Conference Stanford University July 28–31, 1996, pp. 141–150. Stanford Bookstore, Stanford University, CA, USA 28–31 (1996)
Ryan et al., C.: Grammatical evolution: evolving programs for an arbitrary language. In: Banzhaf et al., W. (eds.) EuroGP, LNCS 1391, pp. 83–95. Paris, 14–15 Apr (1998)
Hoai et al., N.X.: Representation and structural difficulty in genetic programming. IEEE Trans. EC, 10(2), 157–166 (2006)
Joshi, A.K., Levy, L.S., Takahashi, M.: Tree adjunct grammars. J. Comput. Syst. Sci. 10, 136–163 (1975)
Ratle, A., Sebag, M.: Avoiding the bloat with probabilistic grammar-guided genetic programming. In: Collet et al., P. (eds), EA 2001, LNCS 2310, pp. 255–266
Shan, Y., McKay, R.I., Baxter, R., Abbass, H., Essam, D., Hoai, N.X.: Grammar model-based program evolution. In: Proceedings of the 2004 IEEE Congress on Evolutionary Computation, pp. 478–485. IEEE Press, Portland, Oregon (2004)
Bosman, P.A.N., de Jong, E.D.: Grammar transformations in an EDA for genetic programming. In: Poli, R., Cagnoni, S., Keijzer, M., Costa, E., Pereira, F., Raidl, G., Upton, S.C., Goldberg, D., Lipson, H., de Jong, E., Koza, J., Suzuki, H., Sawai, H., Parmee, I., Pelikan, M., Sastry, K., Thierens, D., Stolzmann, W., Lanzi, P.L., Wilson, S.W., O’Neill, M., Ryan, C., Yu, T., Miller, J.F., Garibay, I., Holifield, G., Wu, A.S., Riopka, T., Meysenburg, M.M., Wright, A.W., Richter, N., Moore, J.H., Ritchie, M.D., Davis, L., Roy, R., Jakiela, M., (eds.) GECCO 2004 Workshop Proceedings, Seattle, Washington, USA 26–30 (2004)
Langdon, W.B., Poli, R.: Mapping non-conventional extensions of genetic programming. Natural Comput., 7, 21–43 (2008)
Teller, A.: The evolution of mental models. In: Kinnear, Jr., K.E. (ed.) Advances in GP, ch 9, pp. 199–219. MIT Press (1994)
Langdon, W.B.: Genetic Programming and Data Structures: Genetic Programming +Data Structures = Automatic Programming!, volume 1 of Genetic Programming. Kluwer, Boston, (1998)
Yu, T., Clack, C.: PolyGP: A polymorphic genetic programming system in haskell. In: Koza, J.R., Banzhaf, W., Chellapilla, K., Deb, K., Dorigo, M., Fogel, D.B., Garzon, M.H., Goldberg, D.E., Iba, H., Riolo, R. (eds.) Genetic Programming 1998: Proceedings of the Third Annual Conference, pp. 416–421. University of Wisconsin, Madison, Wisconsin, USA, Morgan Kaufmann. (1998)
Binard, F., Felty, A.: Genetic programming with polymorphic types and higher order functions. In: Keijzer, M., Antoniol, G., Congdon, C.B., Deb, K., Doerr, B., Hansen, N., Holmes, J.H., Hornby, G.S., Howard, D., Kennedy, J., Kumar, S., Lobo, F.G., Miller, J.F., Moore, J., Neumann, F., Pelikan, M., Pollack, J., Sastry, K., Stanley, K., Stoica, A., Talbi, El-G., Wegener, I. (eds.) GECCO ’08: Proceedings of the 10th annual conference on Genetic and evolutionary computation, pp. 1187–1194. ACM, Atlanta, GA, USA (2008)
Spector, L., Robinson, A.: Genetic programming and autoconstructive evolution with the push programming language. GP&EM, 3(1), 7–40 (2002)
Spector, L., Klein, J., Keijzer, M.: The push3 execution stack and the evolution of control. In: Beyer, H.-G., O’Reilly, U.-M., Arnold, D.V., Banzhaf, W., Blum, C., Bonabeau, E.W., Cantu-Paz, E., Dasgupta, D., Deb, K., Foster, J.A., de Jong, E.D., Lipson, H., Llora, X., Mancoridis, S., Pelikan, M., Raidl, G.R., Soule, T., Tyrrell, A.M., Watson, J.-P., Zitzler, E. (eds.) GECCO 2005: Proceedings of the 2005 conference on Genetic and evolutionary computation, volume 2, pp. 1689–1696. ACM Press, Washington DC, USA (2005)
Koza, J.R., Andre, D.: Evolution of iteration in genetic programming. In: Fogel, L.J., Angeline, P.J., Baeck, T. (eds.) Evolutionary ProgrammingV: Proceedings of the Fifth Annual Conference on Evolutionary Programming, San Diego, MIT Press, (1996)
Yu, T.: Hierachical processing for evolving recursive and modular programs using higher order functions and lambda abstractions. GP&EM, 2(4), 345–380 (2001)
Whigham, P.A., McKay, R.I.: Genetic approaches to learning recursive relations. In: Yao, X. (ed.) Progress in Evolutionary Computation, LNAI 956, pp. 17–27. Springer (1995)
Brave, S.: Evolving recursive programs for tree search. In: Angeline, P.J., Kinnear, Jr., K.E. (eds.) Advances in Genetic Programming 2, chapter 10, pp. 203–220. MIT Press, Cambridge, MA, USA (1996)
Wong, M.L., Leung, K.S.: Evolving recursive functions for the even-parity problem using genetic programming. In: Angeline, P.J., Kinnear, Jr., K.E. (eds.) Advances in GP 2, ch 11, pp. 221–240. MIT Press (1996)
Yu, T.: A higher-order function approach to evolve recursive programs. In: Yu et al., T. (eds.) GPTP III, ch 7, pp. 93–108. Springer, Ann Arbor, 12-14 May (2005)
Agapitos, A., Lucas, S.M.: Learning recursive functions with object oriented genetic programming. In: Collet, P., Tomassini, M., Ebner, M., Gustafson, S., Ekárt, A. (eds.) Proceedings of the 9th European Conference on Genetic Programming, volume 3905 of Lecture Notes in Computer Science, pp. 166–177. Budapest, Hungary, Springer (2006)
Koza, J.R.: Genetic Programming II: Automatic Discovery of Reusable Programs. MIT Press, Cambridge Massachusetts, (1994)
Koza et al., J.R.: Genetic Programming 3: Darwinian Invention and Problem Solving. Morgan Kaufman (1999)
Angeline, P.J., Pollack, J.: Evolutionary module acquisition. In: Fogel, D., Atmar, W. (eds.) Proceedings of the Second Annual Conference on Evolutionary Programming, pp. 154–163. La Jolla, CA, USA (1993)
Kinnear, K.E. Jr.: Alternatives in automatic function definition: A comparison of performance. In: Kinnear, K.E. Jr., (ed.) Advances in Genetic Programming, chapter 6, pp. 119–141. MIT Press, (1994)
Walker, J.A., Miller, J.F.: The automatic acquisition, evolution and reuse of modules in cartesian genetic programming. IEEE Trans. EC 12(4), 397–417 (2008)
Spector, L.: Simultaneous evolution of programs and their control structures. In: Angeline, P.J., Kinnear, K.E. Jr.,: (eds.) Advances in Genetic Programming 2, chapter 7, pp. 137–154. MIT Press, Cambridge, MA, USA (1996)
Bruce, W.S.: Automatic generation of object-oriented programs using genetic programming. In: Koza et al., J.R. (eds.) GP 1996, pp. 267–272. MIT Press, Stanford, 28–31 Jul 1996
Lucas, S.: Exploiting reflection in object oriented genetic programming. In: Keijzer et al., M. (eds.) EuroGP, LNCS 3003, pp. 369–378. Springer 5–7 Apr (2004)
Briggs, F., O’Neill, M.: Functional genetic programming with combinators. In: Pham et al., T.L. (eds.) Proceedings of the Third Asian-Pacific workshop on Genetic Programming, ASPGP, pp. 110–127, Military Technical Academy, Hanoi, Vietnam (2006)
Banzhaf, W.: Genotype-phenotype-mapping and neutral variation – A case study in genetic programming. In: Davidor, Y., Schwefel, H.-P., Männer, R. (eds.) Parallel Problem Solving from Nature III, volume 866 of LNCS, pp. 322–332, Springer-Verlag, Jerusalem (1994)
Jacob, C.: Genetic L-system programming. In: Davidor, Y., Schwefel, H.-P., Männer, R. (eds.) Parallel Problem Solving from Nature III, volume 866 of LNCS, pp. 334–343. Springer-Verlag, Jerusalem (1994)
Spector, L., Stoffel, K.: Ontogenetic programming. In: Koza et al., J.R. (eds.) GP-96, pp. 394–399. Stanford, MIT Press 28–31 Jul (1996)
Harding, S.L., Miller, J.F., Banzhaf, W.: Self-modifying cartesian genetic programming. In: Thierens, D., Beyer, H.-G., Bongard, J., Branke, J., Clark, J.A., Cliff, D., Congdon, C.B., Deb, K., Doerr, B., Kovacs, T., Kumar, S., Miller, J.F., Moore, J., Neumann, F., Pelikan, M., Poli, R., Sastry, K., Stanley, K.O., Stutzle, T., Watson, R.A., Wegener, I. (eds.) GECCO ’07: Proceedings of the 9th annual conference on Genetic and evolutionary computation, volume 1, pp. 1021–1028. ACM Press, London (2007)
Gruau, F.: Genetic micro programming of neural networks. In: Kinnear, Jr., Kenneth, E. (ed.) Advances in Genetic Programming, chapter 24, pp. 495–518. MIT Press, (1994)
Koza, J.R., Keane, M.A., Streeter, M.J., Mydlowec, W., Yu, J., Lanza, G.: Genetic Programming IV: Routine Human-Competitive Machine Intelligence. Kluwer Academic Publishers, (2003)
Gottlieb, G.: Individual development and evolution: The genesis of novel behavior. Oxford University Press, New York (1992)
Gottlieb, G.: Individual development and evolution: The genesis of novel behavior. Oxford University Press, New York (1992)
Miller, J.F.: Evolving developmental programs for adaptation, morphogenesis, and self-repair. In: Banzhaf et al., W. (eds), ECAI, LNAI 2801, pp. 256–265. Springer 14–17 Sep (2003)
Angeline, P.J.: Adaptive and self-adaptive evolutionary computations. In: Palaniswami, M., Attikiouzel, Y. (eds.) Computational Intelligence: A Dynamic Systems Perspective, pp. 152–163. IEEE Press, (1995)
Meyer-Nieberg, S., Beyer, H.-G.: Self-adaptation in evolutionary algorithms. Parameter Setting in Evolutionary Algorithm. Springer (2006)
Schmidhuber, J.: Evolutionary principles in self-referential learning. on learning now to learn: the meta-meta-meta...-hook. Diploma thesis, Technische Universitat Munchen, Germany, 14 May (1987)
Edmonds, B.: Meta-genetic programming: Co-evolving the operators of variation. CPM Report 98-32, Centre for Policy Modelling, Manchester Metropolitan University, UK, AytounSt., Manchester, M1 3GH. UK, (1998)
Lohn et al., J.: Evolutionary antenna design for a NASA spacecraft. In: O’Reilly et al., U.-M. eds. GPTP II, ch 18, pp. 301–315. Springer, Ann Arbor, 13–15 May 2004
Langdon, W.B., Buxton, B.F.: Genetic programming for mining DNA chip data from cancer patients. Genet. Prog. Evol. Mach., 5(3), 251–257, (2004)
Spector, L., Barnum, H., Bernstein, H.J., Swamy, N.: Finding a betterthan-classical quantumAND/OR algorithm using genetic programming. In: Angeline, P.J., Michalewicz, Z., Schoenauer, M., Yao, X., Zalzala, A. (eds.) Proceedings of the Congress on Evolutionary Computation, volume
Spector, L., Bernstein, H.J.: Communication capacities of some quantum gates, discovered in part through genetic programming. In: Shapiro, Jeffrey H., Hirota, O. (eds) Proceedings of the Sixth International Conference on Quantum Communication, Measurement, and Computing (QCMC), pp. 500–503. Rinton Press, (2003)
Jordaan, E., Kordon, A., Chiang, L., Smits, G.: Robust inferential sensors based on ensemble of predictors generated by genetic programming. In: Yao, X., Burke, E., Lozano, J.A., Smith, J., Merelo-Guervós, J.J., Bullinaria, J.A., Rowe, J., Tiňo Ata Kabán, P., Schwefel, H.-P. (eds.) Parallel Problem Solving from Nature – PPSN VIII, volume 3242 of LNCS, pp. 522–531. Springer-Verlag Birmingham, UK (2004)
Langdon, W.B., Buxton, B.F.: Genetic programming for mining DNA chip data from cancer patients. GP&EM, 5(3), 251–257 (2004)
Hampo, R.J., Marko, K.A.: Application of genetic programming to control of vehicle systems. In: Proceedings of the Intelligent Vehicles ’92 Symposium, pp. 191–195. IEEE, Detroit, Mi, USA (1992)
D. H. and S.C. Roberts. Incident detection on highways. In U.-M. O’Reilly et al., eds., GPTP II, ch 16, pp 263–282. Springer, Ann Arbor, 13-15 May (2004)
Ross et al., B.J.: Hyperspectral image analysis using genetic programming. Appl. Soft Comput. 5(2), 147–156 (2005)
Zhang, M., Smart, W., Using gaussian distribution to construct fitness functions in genetic programming for multiclass object classification. Pattern. Recognit. Lett., 27(11), 1266–1274, Evolutionary Computer Vision and Image Understanding. (2006)
Cilibrasi, R., Vitanyi, P.M.B.: Clustering by compression. IEEE Trans. Inf. Theory, 51(4), 1523–1545 (2005)
Klassen, T.J., Heywood, M.I.: Towards the on-line recognition of arabic characters. In Proceedings of the 2002 International Joint Conference on Neural Networks IJCNN’02, pp. 1900–1905. IEEE Press, Hilton Hawaiian Village Hotel, Honolulu, Hawaii, (2002)
De Stefano et al., C.: Character preclassification based on genetic programming. Pattern Recogn. Lett. 23(12), 1439–1448 (2002)
Teredesai, A., Govindaraju, V.: GP-based secondary classifiers. Pattern Recogn. 38(4), 505–512 (2005)
Parkins, A.D., Nandi, A.K.: Genetic programming techniques for hand written digit recognition. Signal Process., 84(12), 2345–2365 Dec (2004)
Quintana et al., M.I.: Morphological algorithm design for binary images using genetic programming. GP&EM, 7(1), 81–102 (2006)
Martin, M.C. Evolving visual sonar: Depth from monocular images. Pattern RecognitionLetters, 27(11), 1174–1180 Evolutionary Computer Vision and Image Understanding. (2006)
Usman et al., I.: Image authenticity and perceptual optimization via genetic algorithm and a dependence neighborhood. IJAMCS, 4(1), 615–620 (2007)
Chen, S.-H., Liao, C.-C.: Agent-based computational modeling of the stock price-volume relation. Information Sciences, 170(1), 75–100 (2005)
Yu, T., Chen, S.-H.: Using genetic programming with lambda abstraction to find technical trading rules. In: Computing in Economics and Finance, University of Amsterdam, (2004)
Neely et al., C.J.: Is technical analysis in the foreign exchange market profitable? A GP approach. J. Finan. Quant. Anal. 32(4), 405–426 (1997)
Marney, J.P., Miller, D., Fyfe, C., Tarbert, H.F.E.: Risk adjusted returns to technical trading rules: a genetic programming approach. In: 7th International Conference of Society of Computational Economics, Yale, 28–29 (2001)
Neely et al., C.J.: The adaptive markets hypothesis: evidence from the foreign exchange market. Working Paper 2006-046B, Federal Reserve Bank of St. Louis Rev (2007)
Kaboudan, M.: Extended daily exchange rates forecasts using wavelet temporal resolutions. New Math. Nat. Comput. 1, 79–107 (2005)
Tsang et al., E.P.K.: EDDIE beats the bookies. Softw. Pract. Exper., 28(10), 1033–1043 (1998)
Austin et al., M.P.: Adaptive systems for foreign exchange trading. Quant. Finan., 4(4), 37–45 (2004)
Pillay, N.: Evolving solutions to ASCII graphics programming problems in intelligent programming tutors. In: Akerkar, R. ed. International Conference on Applied Artificial Intelligence (ICAAI’2003), pp. 236–243. Fort Panhala, Kolhapur, India TMRF. 15–16 Dec (2003)
Kordon, A.: Evolutionary computation in the chemical industry. In: Yu et al., T. (eds.) Evolutionary Computation in Practice, ch 11, pp. 245–262. Springer (2008)
Kovacic, M., Balic, J.: Evolutionary programming of a CNC cutting machine. Int. J. Advan. Manufact. Technol., 22(1–2), 118–124 (2003)
Deschaine, L.: Using information fusion, machine learning, and global optimisation to increase the accuracy of finding and understanding items interest in the subsurface. GeoDrill. Int. 122, 30–32 May (2006)
Barriere, O., Lutton, E., Baudrit, C., Sicard, M., Pinaud, B., Perrot, N.: Modeling human expertise on a cheese ripening industrial process using GP. In: Rudolph, G. (ed.) PPSN X, volume 5199 of LNCS, Springer, Dortmund (2008)
Dassau et al., E.: Modeling and temperature control of rapid thermal processing. Comput. Chem. Eng., 30(4), 686–697 (2006)
Rodriguez-Vazquez et al., K.: Identifying the structure of nonlinear dynamic systems using multiobjective genetic programming. IEEE Trans. Syst., Man Cyberne., Part A, 34(4), 531–545 (2004)
Kell, D.: Defence against the flood. Bioinformatics World, pp. 16–18. (2002)
Moore et al., J.H.: Symbolic discriminant analysis of microarray data in automimmune disease. Genet. Epidemiol., 23, 57–69 (2002)
Barrett, S.J., Langdon, W.B.: Advances in the application of machine learning techniques in drug discovery, design and development. In: Tiwari, A., Knowles, J., Avineri, E., Dahal, K., Roy, R. (eds.) Applications of Soft Computing:Recent Trends, Advances in Soft Computing, pp. 99–110. On the World Wide Web, Springer, (2006)
Bains et al., W.: Evolutionary computational methods to predict oral bioavailability QSPRs. Curr. Opin. Drug Discov. Develop., 5(1), 44–51 (2002)
Fukunaga, A.: Automated discovery of composite SAT variable selection heuristics. In: AAAI, pp. 641–648. (2002)
Keller, R.E., Poli, R.: Cost-benefit investigation of a genetic-programming hyperheuristic. In Evolution Artificielle, 8th International Conference, Lecture Notes in Computer Science, Tours, Springer, France (2007)
Azaria, Y., Sipper, M.: GP-gammon: genetically programming backgammon players. Gene. Program. Evolvable Mach., 6(3), 283–300 (2005)
Funes, P., Sklar, E., Juille, H., Pollack, J.: Animal-animat coevolution: using the animal population as fitness function. In: Pfeifer et al., R. (eds.) SAB, pp. 525–533. Zurich, Aug 17–21 (1998). MIT Press
Machado, P., Romero, J. (eds.): The Art of Artificial Evolution. Springer (2008)
Spector, L., Alpern, A.: Criticism, culture, and the automatic generation of artworks. In: AAAI-94, pp. 3–8. Seattle, Washington, USA AAAI Press/MIT Press (1994)
Takagi, H.: Interactive evolutionary computation: Fusion of the capabilities of EC optimization and human evaluation. Proc. IEEE, 89(9), 1275–1296 (2001)
Langdon, W.B.: Global distributed evolution of L-systems fractals. In: Keijzer et al., M. (eds.) EuroGP’2004, LNCS 3003, pp. 349–358. Coimbra, Portugal, Springer 5–7 Apr (2004)
Reynolds, C.W.: Flocks, herds, and schools: a distributed behavioral model. SIGGRAPH Comput. Graph., 21(4), 25–34 (1987)
Koza et al., J.R.: Automatic creation of human-competitive programs and controllers by means of genetic programming. GP&EM, 1(1/2), 121–164 (2000)
Koza, J.R., Al-Sakran, S.H., Jones, L.W.: Automated re-invention of six patented optical lens systems using genetic programming. In: Beyer, H.-G., O’Reilly, U.-M., Arnold, D.V., Banzhaf, W., Blum, C., Bonabeau, E.W., Cantu-Paz, E., Dasgupta, D., Deb, K., Foster, J.A., de Jong, E.D., Lipson, H., Llora, X., Mancoridis, S., Pelikan, M., Raidl, G.R., Soule, T., Tyrrell, A.M., Watson, J.-P., Zitzler, E. (eds.) GECCO 2005: Proceedings of the 2005 conference on Genetic and evolutionary computation, volume 2, pp. 1953–1960. ACM Press, Washington DC, USA (2005)
Kinnear, K.E., Jr.: A perspective on the work in this book. In: Kinnear, Jr., K.E. (ed.) Advances in Genetic Programming, chapter 1, pp. 3–19. MIT Press, (1994)
Corney, D.P.A.: Intelligent analysis of small data sets for food design. Ph.D. thesis, University College, London (2002)
Daida, J.M., Hilss, A.M., Ward, D.J., Stephen, L.: Long. Visualizing tree structures in genetic programming. Genet. Prog. Evol. Mach., 6(1), 79–110 (2005)
McPhee, N.F., Ohs, B., Hutchison, T., Semantic building blocks in genetic programming. In: O’Neill, M., Vanneschi, L., Gustafson, S., Alcazar, A.I.E., De Falco, I., Cioppa, A.D., Tarantino, E. (eds.) Proceedings of the 11th European Conference on Genetic Programming, EuroGP 2008,volume 4971 of Lecture Notes in Computer Science, pp. 134–145. Springer, Naples (2008)
Crane, E.F., McPhee, N.F.: The effects of size and depth limits on tree based genetic programming. In: Yu et al., T. (eds.) Genetic Programming Theory and Practice III, ch 15, pp. 223–240. Springer, Ann Arbor, 12–14 May (2005)
Spector, L., Klein, J.: Trivial geography in genetic programming. In: Yu et al., T. (eds.) GPTP III, ch 8, pp. 109–123. Springer, Ann Arbor, 12–14 May (2005)
Gelly, S., Teytaud, O., Bredeche, N., Schoenauer, M.: Universal consistency and bloat in GP. Issue on New Methods in Machine Learning. Theory Appl. Rev. d’Intelligence Artif., 20(6), 805–827 (2006)
Yu, T., Davis, D., Baydar, C., Roy, R. (eds.) Evolutionary Computation in Practice, volume 88 of Studies in Computational Intelligence. Springer, (2008)
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Langdon, W.B., McKay, R.I., Spector, L. (2010). Genetic Programming. In: Gendreau, M., Potvin, JY. (eds) Handbook of Metaheuristics. International Series in Operations Research & Management Science, vol 146. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1665-5_7
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