Abstract
This paper examines the effect of cultural learning on a population of neural networks. We compare the genotypic and phenotypic diversity of populations employing only population learning and of populations using both population and cultural learning in two types of dynamic environment: one where a single change occurs and one where changes are more frequent. We show that cultural learning is capable of achieving higher fitness levels and maintains a higher level of genotypic and phenotypic diversity.
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References
Brown, G.: Diversity in Neural Network Ensembles. PhD thesis, University of Birmingham (2003)
Cangelosi, A., Parisi, D.: The emergence of a language in an evolving population of neural networks. Technical Report NSAL–96004, National Research Council, Rome (1996)
Chomsky, N.: On the nature of language. In: Origins and evolution of language and speech, vol. 280, pp. 46–57. Annals of the New York Academy of Science, New York (1976)
Denaro, D., Parisi, D.: Cultural evolution in a population of neural networks. In: Marinaro, M., Tagliaferri, R. (eds.) Neural Nets Wirn-96, pp. 100–111. Springer, New York (1996)
Kendall, G., Burke, E.K., Gustafson, S.: Diversity in genetic programming: an analysis of measures and correlation with fitness. IEEE Trans. Evolutionary Computation 8(1), 47–62 (2004)
Grefenstette, J.J.: Genetic algorithms for dynamic environments. In: Maenner, R., Manderick, B. (eds.) Parallel Problem Solving from Nature, vol. 2, pp. 137–144 (1992)
Hutchins, E., Hazlehurst, B.: Learning in the cultural process. In: Langton, C., et al. (eds.) Artificial Life II, pp. 689–706. MIT Press, Cambridge (1991)
Hutchins, E., Hazlehurst, B.: How to invent a lexicon: The development of shared symbols in interaction. In: Gilbert, N., Conte, R. (eds.) Artificial Societies: The Computer Simulation of Social Life, pp. 157–189. UCL Press, London (1995)
Kitano, H.: Designing neural networks using genetic algorithm with graph generation system. Complex Systems 4, 461–476 (1990)
MacLennan, B., Burghardt, G.: Synthetic ethology and the evolution of cooperative communication. Adaptive Behavior 2(2), 161–188 (1993)
Menczer, F.: Changing latent energy environments: A case for the evolution of plasticity. Technical Report CS94-336 (1994)
Miller, G.F., Todd, P.M., Hedge, S.U.: Designing neural networks using genetic algorithms. In: Proceedings of the Third International Conference on Genetic Algorithms and Their Applications, pp. 379–384 (1989)
Nolfi, S., Parisi, D.: Learning to adapt to changing environments in evolving neural networks. Technical Report 95-15, Institute of Psychology, National Research Council, Rome, Italy (1995)
Opitz, D.W., Shavlik, J.W.: Generating accurate and diverse members of a neural-network ensemble. In: Touretzky, D.S., Mozer, M.C., Hasselmo, M.E. (eds.) Advances in Neural Information Processing Systems, vol. 8, pp. 535–541. The MIT Press, Cambridge (1996)
Sasaki, T., Tokoro, M.: Adaptation toward changing environments: Why darwinian in nature. In: Husbands, P., Harvey, I. (eds.) Fourth European Conference on Artificial Life, pp. 145–153. MIT Press, Cambridge (1997)
Spector, L.: Genetic programming and AI planning systems. In: Proceedings of Twelfth National Conference on Artificial Intelligence, Seattle, Washington, USA, pp. 1329–1334. AAAI Press/MIT Press (1994)
Steels, L.: The synthetic modeling of language origins. In: Evolution of Communication, pp. 1–34 (1997)
Yao, X., Liu, Y., Higuchi, T.: Evolutionary ensembles with negative correlation learning. IEEE Transactions on Evolutionary Computation 4(4), 380–387 (2000)
Yanco, H., Stein, L.: An adaptive communication protocol for cooperating mobile robots. In: From Animals to Animats 2. Proceedings of the second International Conference on Simulation of Adaptive Behavior, pp. 478–485. MIT Press, Cambridge (1993)
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Curran, D., O’Riordan, C. (2005). Measuring Diversity in Populations Employing Cultural Learning in Dynamic Environments. In: Capcarrère, M.S., Freitas, A.A., Bentley, P.J., Johnson, C.G., Timmis, J. (eds) Advances in Artificial Life. ECAL 2005. Lecture Notes in Computer Science(), vol 3630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553090_39
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DOI: https://doi.org/10.1007/11553090_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28848-0
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