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2017 | OriginalPaper | Chapter

Cartesian Genetic Programming in an Open-Ended Evolution Environment

Authors : António Simões, Tiago Baptista, Ernesto Costa

Published in: Progress in Artificial Intelligence

Publisher: Springer International Publishing

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Abstract

In this paper we describe and analyze the use of the Cartesian Genetic Programming method to evolve Artificial Neural Networks (CGPANN) in an open-ended evolution scenario. The issue of open-ended evolution has for some time been considered one of the open problems in the field of Artificial Life. In this paper we analyze the capabilities of CGPANN to evolve behaviors in a scenario without artificial selection, more specifically, without the use of explicit fitness functions. We use the BitBang framework and one of its example scenarios as a proof of concept. The results obtained in these first experiments show that it is indeed possible to evolve CGPANN brains, in an open-ended environment, without any explicit fitness function. We also present an analysis of different parameter configurations for the CGPANN when used in this type of scenario.

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previous chapter GAVGA: A Genetic Algorithm for Viral Genome Assembly
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Literature
1.
Banzhaf, W., Baumgaertner, B., Beslon, G., Doursat, R., Foster, J.A., McMullin, B., de Melo, V.V., Miconi, T., Spector, L., Stepney, S., White, R.: Defining and simulating open-ended novelty: requirements, guidelines, and challenges. Theory Biosci. 135(3), 1–31 (2016)CrossRef
2.
Baptista, T.: Complexity and emergence in societies of agents. Ph.D. thesis, University of Coimbra, Coimbra, July 2012
3.
Baptista, T., Menezes, T., Costa, E.: Bitbang: a model and framework for complexity research. In: Proceedings of the European Conference on Complex Systems 2006, Oxford, UK, p. 73, September 2006
4.
Bedau, M.A., McCaskill, J.S., Packard, N.H., Rasmussen, S., Adami, C., Green, D.G., Ikegami, T., Kaneko, K., Ray, T.S.: Open problems in artificial life. Artif. Life 6(4), 363–376 (2000)CrossRef
5.
Channon, A.: Three evolvability requirements for open-ended evolution. In: Maley, C.C., Boudreau, E. (eds.) Artificial Life VII Workshop Proceedings, Portland, USA, pp. 39–40 (2000)
6.
Channon, A.: Unbounded evolutionary dynamics in a system of agents that actively process and transform their environment. Genet. Program. Evolvable Mach. 7(3), 253–281 (2006)CrossRef
7.
Floreano, D., Durr, P., Mattiussi, C.: Neuroevolution: from architectures to learning. Evol. Intell. 1, 47–62 (2008)CrossRef
8.
Khan, M.M., Khan, G.M., Miller, J.F.: Evolution of neural networks using Cartesian genetic programming. In: IEEE Congress on Evolutionary Computation, pp. 1–8, July 2010
9.
McCulloch, W., Pitts, W.: A logical calculus of ideas immanent in nervous activity. Bull. Math. Biophys. 5(3), 115–133 (1943)MathSciNetCrossRef
10.
Miller, J.F. (ed.): Cartesian Genetic Programming. Natural Computing Series, 1st edn. Springer, Heidelberg (2011)
11.
Miller, J.F., Thomson, P.: Cartesian Genetic Programming. Genet. Program. 10802(3), 121–132 (2000)
12.
Standish, R.K.: Open-ended artificial evolution. Int. J. Comput. Intell. Appl. 3(2), 167–175 (2003)CrossRef
13.
Stanley, K.O.: Efficient evolution of neural networks through complexification. Ph.D. thesis, The University of Texas at Austin, November 2004
14.
Stanley, K.O., Miikkulainen, R.: Efficient reinforcement learning through evolving neural network topologies. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2002), San Francisco, US, p. 9 (2002)
15.
Taylor, T., Bedau, M.A., Channon, A., Ackley, D., Banzhaf, W., Beslon, G., Dolson, E., Froese, T., Hickinbotham, S., Ikegami, T., McMullin, B., Packard, N., Rasmussen, S., Virgo, N., Agmon, E., Clark, E., McGregor, S., Ofria, C., Ropella, G., Spector, L., Stanley, K.O., Stanton, A., Timperley, C., Vostinar, A., Wiser, M.: Open-ended evolution: perspectives from the OEE workshop in York. Artif. Life 22(3), 408–423 (2016)CrossRef
16.
Turner, A.: Evolving artificial neural networks using Cartesian genetic programming. Ph.D. thesis, University of York, York, September 2015
17.
Turner, A., Miller, J.F.: Cartesian genetic programming: why no bloat? In: 2013 Proceedings of the Thirty-third SGAI International Conference on Artificial Intelligence, pp. 193–204 (2014)
18.
Turner, A., Miller, J.F.: Introducing a cross platform open source Cartesian genetic programming library. Genet. Program. Evolvable Mach. 16, 83–91 (2015)CrossRef
19.
Turner, A.J., Miller, J.F.: Cartesian genetic programming encoded artificial neural networks: a comparison using three benchmarks. In: Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation, GECCO 2013, NY, USA, pp. 1005–1012 (2013). http://​doi.​acm.​org/​10.​1145/​2463372.​2463484
20.
Vassilev, V.K., Fogarty, T.C., Miller, J.F.: Smoothness, ruggedness and neutrality of fitness landscapes: from theory to application. In: Ghosh, A., Tsutsui, S. (eds.) Advances in Evolutionary Computing. Natural Computing Series, pp. 3–44. Springer, Berlin (2003). doi:10.​1007/​978-3-642-18965-4_​1
21.
Vassilev, V.K., Miller, J.F.: The advantages of landscape neutrality in digital circuit evolution. In: Miller, J., Thompson, A., Thomson, P., Fogarty, T.C. (eds.) ICES 2000. LNCS, vol. 1801, pp. 252–263. Springer, Heidelberg (2000). doi:10.​1007/​3-540-46406-9_​25CrossRef
22.
Yao, X.: Evolving artificial neural networks. In: Proceedings of the IEEE, pp. 1423–1447, February 1999
Metadata
Title
Cartesian Genetic Programming in an Open-Ended Evolution Environment
Authors
António Simões
Tiago Baptista
Ernesto Costa
Copyright Year
2017
Book
Progress in Artificial Intelligence

Print ISBN: 978-3-319-65339-6

Electronic ISBN: 978-3-319-65340-2

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-65340-2_34

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