Cogprints

What does it take to evolve behaviorally complex organisms?

Calabretta, Raffaele and Di Ferdinando, Andrea and Wagner, Günter P. and Parisi, Domenico (2001) What does it take to evolve behaviorally complex organisms? [Departmental Technical Report] (In Press)

Full text available as:

[img]PDF
309Kb

Abstract

What genotypic features explain the evolvability of organisms that have to accomplish many different tasks? The genotype of behaviorally complex organisms may be more likely to encode modular neural architectures because neural modules dedicated to distinct tasks avoid neural interference, i.e., the arrival of conflicting messages for changing the value of connection weights during learning. However, if the connection weights for the various modules are genetically inherited, this raises the problem of genetic linkage: favorable mutations may fall on one portion of the genotype encoding one neural module and unfavorable mutations on another portion encoding another module. We show that this can prevent the genotype from reaching an adaptive optimum. This effect is different from other linkage effects described in the literature and we argue that it represents a new class of genetic constraints. Using simulations we show that sexual reproduction can alleviate the problem of genetic linkage by recombining separate modules all of which incorporate either favorable or unfavorable mutations. We speculate that this effect may contribute to the taxonomic prevalence of sexual reproduction among higher organisms. In addition to sexual recombination, the problem of genetic linkage for behaviorally complex organisms may be mitigated by entrusting evolution with the task of finding appropriate modular architectures and learning with the task of finding the appropriate connection weights for these architectures.

Item Type:Departmental Technical Report
Keywords:genetic linkage, neural interference, modular neural networks, genetic algorithms
Subjects:Biology > Evolution
Computer Science > Neural Nets
ID Code:2324
Deposited By:Di Ferdinando, Andrea
Deposited On:16 Jul 2002
Last Modified:11 Mar 2011 08:54

References in Article

Select the SEEK icon to attempt to find the referenced article. If it does not appear to be in cogprints you will be forwarded to the paracite service. Poorly formated references will probably not work.

Calabretta, R., Parisi, D., in press. Evolutionary connectionism and mind/brain modularity. In: Callebaut, W., Rasskin-Gutman, D. (Eds.), Modularity. Understanding the development and evolution of complex natural systems. The MIT Press, Cambridge, MA.

Crow, J. F., Kimura, M., 1965. Evolution in sexual and asexual populations. American Naturalist 99, 439-450.

De Visser, J.A.G.M., Zeyl, C. W., Gerrish, P. J., Blanchard, J. L., Lenski, R. E., 1999. Diminishing returns from mutation supply rate in asexual populations. Science, 283(5398), 404-406.

Di Ferdinando, A., Calabretta, R., Parisi, D., 2001. Evolving modular architectures for neural networks. In: French, R. M., Sougné, J. P. (Eds.), Connectionist models of learning, development and evolution, pp. 253-262. Springer-Verlag, London.

Ellis, A.W., Lambon Ralph, M.A., 2000. Age of acquisition effects in adult lexical processing reflect loss of plasticity in maturing systems: Insights from connectionist networks. Journal of Experimental Psychology: Learning, Memory & Cognition 26, 1103-1123.

Elman, J. L., Bates, E. A., Johnson, M. H., Karmiloff-Smith, A., Parisi, D., Plunkett, K., 1996. Rethinking innateness. A connectionist perspective on development. The MIT Press, Cambridge, MA.

Felsenstein, J., 1974. The evolutionary advantage of recombination. Genetics 78, 737-756.

Futuyma, D. J., 1998. Evolutionary Biology. Sinauer, Sunderland, MA.

Haigh, J., 1978. The accumulation of deleterious genes in a population - Muller's Ratchet. Theor. Pop. Biol. 14: 251-267.

Holland, J. H., 1992. Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. The MIT Press, Cambridge, MA.

Maynard-Smith, J., 1978. The evolution of sex. Cambridge University Press, Cambridge.

Milner, A. D. & Goodale, M. A. 1998. The visual brain in action. PSYCHE, 4(12) (http://psyche.cs.monash.edu.au/v4/psyche-4-12-milner.html).

Rueckl, J. G., Cave, K. R., Kosslyn, S. M., 1989. Why are “what” and “where” processed by separate cortical visual systems? A computational investigation. Journal of Cognitive Neuroscience 1, 171-186.

Rumelhart, D., McClelland, J., 1986. Parallel Distributed Processing: Explorations in the Microstructure of Cognition. The MIT Press, Cambridge, MA.

Smith, M. A., Cottrell, G. W., Anderson, K. L., in press. The early word catches the weights. In: Advances in Neural Information Processing Systems 12. The MIT Press, Cambridge, MA.

Ungerleider, L. G. & Mishkin, M. 1982. Two cortical visual systems. In Ingle, D. J., Goodale, M. A. & Mansfield, R. J. W. (Eds.), The Analysis of Visual Behavior. The MIT Press, Cambridge, MA.

Wagner, G. P., Mezey, J., Calabretta, R., in press. Natural Selection and the origin of modules. In: Callebaut, W., Rasskin-Gutman, D. (Eds.), Modularity. Understanding the development and evolution of complex natural systems. The MIT Press, Cambridge, MA.

Wagner, G. P., and W. Gabriel, 1990. Quantitative variation in finite parthenogenetic populations: What stops Muller's ratchet in the absence of recombination? Evolution 44, 715-731.

Waxman, D., and J. R. Peck, 1999. Sex and adaptation in a changing environment. Genetics 153, 1041-1053.

Yao, X., 1999. Evolving artificial neural networks. Proceedings of the IEEE 87, 1423-1447.

Metadata

Repository Staff Only: item control page