Abstract
This paper describes recent attempts to understand the evolution of language in humans and argues that useful lessons can be learned from this analysis by designers of hybrid symbolic/connectionist systems. A specification is sketched out for a biologically grounded hybrid system motivated by our understanding of both the evolution and development of symbolisation in humans.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Chomsky, N.: Knowledge of language. Praeger, New York (1986)
Christiansen, M.H., Chater, N.: Generalisation and connectionist language learning. Mind and Language 9, 273–287 (1994)
Cruikshank, S.J., Weinberger, N.M.: Evidence for the Hebbian hypothesis in experience-dependent physiological plasticity of neocortex: A critical review. Brain Research Reviews 22, 191–228 (1996)
Deacon, T.: The symbolic species: The co-evolution of language and the human brain. The Penguin Group, London (1997)
Elman, J.L.: Learning and development in neural networks: The importance of starting small. Cognition 48, 71–99 (1993)
Fodor, J.A., Pylyshyn, Z.W.: Connectionism and cognitive architecture: A critical analysis. Cognition 28, 3–71 (1988)
Gold, E.L.: Language identification in the limit. Information and Control 16, 447–474 (1967)
Greenfield, P., Nelson, K., Saltzman, E.: The development of rule-bound strategies for manipulating seriated cups: A parallel between action and grammar. Cognitive Psychology 3, 291–310 (1972)
Greenfield, P.: Language, tool and brain: The ontogeny and phylogeny of hierarchically organized sequential behavior. Behavioral and Brain Sciences 14, 531–595 (1991)
Hadley, R.F.: Systematicity in connectionist language learning. Mind and Language 9, 247–271 (1994)
Hadley, R.F., Hayward, M.B.: Strong semantic systematicity from Hebbian connectionist learning. Mind and Machines 7, 1–37 (1997)
Pinker, S.: The language instinct: how the mind creates language. William Morrow, New York (1994)
Pollack, J.B.: Recursive distributed representations. Artificial Intelligence 46, 177–105 (1990)
Rebotier, T.P., Elman, J.L.: Explorations with the dynamic wave model. In: Touretsky, D., Mozer, M., Haselmo, M. (eds.) Advances in Neural Information Processing Systems 8. MIT Press, Cambridge (1996)
Reilly, R.G.: The relationship between object manipulation and language development in Broca’s area: A connectionist simulation of Greenfield’s hypothesis. Behavioral and Brain Sciences (in press)
Reilly, R.G.: Cortical software refuse: A neural basis for creative cognition. In: Veale, T. (ed.) Computational Models of Creative Computation, pp. 36–42 (1998)
Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning internal representations by error propagation. In: Rumelhart, D.E., McClelland, J.L., The PDP Research Group (eds.) Parallel distributed processing. Explorations in the microstructure of cognition: Foundations, vol. 1, pp. 318–362. MIT Press, Cambridge (1986)
Sejnowski, T.J.: Open questions about computation in the cerebral cortex. In: McClelland, J.L., Rumelhart, D.E., The PDP Research Group (eds.) Parallel distributed processing. Explorations in the microstructure of cognition. Psychological and biological models, vol. 2, pp. 372–389. MIT Press, Cambridge (1986)
Savage–Rumbaugh, E.S., Lewin, R.: Kanzi: The ape at the brink of the human mind. John Wiley, New York (1994)
Shrager, J., Johnson, M.H.: Dynamic plasticity influences the emergence of function in a simple cortical array. Neural Networks 9, 1119–1129 (1996)
Thatcher, R.W.: Cyclic cortical reorganization during early childhood. Brain and Cognition 20, 24–50 (1992)
Van Gelder, T.: Compositionality: A connectionist variation on a classical theme. Cognitive Science 14, 355–384 (1990)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Reilly, R.G. (2000). Evolution of Symbolisation: Signposts to a Bridge between Connectionist and Symbolic Systems. In: Wermter, S., Sun, R. (eds) Hybrid Neural Systems. Hybrid Neural Systems 1998. Lecture Notes in Computer Science(), vol 1778. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10719871_25
Download citation
DOI: https://doi.org/10.1007/10719871_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67305-7
Online ISBN: 978-3-540-46417-4
eBook Packages: Springer Book Archive