Skip to main content
Log in

Connectionism and artificial intelligence as cognitive models

  • Published:
AI & SOCIETY Aims and scope Submit manuscript

Abstract

The current renewal of connectionist techniques using networks of neuron-like units has started to have an influence on cognitive modelling. However, compared with classical artificial intelligence methods, the position of connectionism is still not clear. In this article artificial intelligence and connectionism are systematically compared as cognitive models so as to bring out the advantages and shortcomings of each. The problem of structured representations appears to be particularly important, suggesting likely research directions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Barr, A., Cohen, P. R. and Feigenbaum, E. A. (1982).The Handbook of Artificial Intelligence. William Kaufman.

  • Carbonell, J., Michalski, R. and Mitchell, T. (eds). (1983).Machine Learning. Tioga.

  • Charniak, E., Riesbeck, C. K. and McDermott, D. V. (1980).Artificial Intelligence Programming. Lawrence Erlbaum.

  • Davies, M. (1989). Connectionism, modularity and tacit knowledge,British Journal of the Philosophy of Science, 40.

  • Doyle, J. (1979). A truth maintenance system,Artificial Intelligence, 12.

  • Erman, L. D., Hayes-Roth, F., Lesser, V. and Reddy, D. R. (1980). The HEARSAY-II speech understanding system,ACM Computing Surveys, 12 (2).

  • Feldman, J. A. and Ballard, D. H. (1982). Connectionist models and their properties,Cognitive Science, 6.

  • Fodor, J. A. (1975).The Language of Thought. Harvard University Press.

  • Fodor, J. A. (1980). Methodological solipsism considered as a research strategy in cognitive science,Behavioral and Brain Sciences, 3.

  • Fodor, J. A. (1987).Psychosemantics. MIT Press.

  • Fodor, J. A. and Pylyshyn, Z. W. (1988). Connectionism and cognitive architecture: a critical analysis.Cognition, 28 (1–2).

    Google Scholar 

  • Gardner, H. (1985).The Mind's New Science. Basic Books.

  • Haugeland, J. (1985).Artificial Intelligence: The Very Idea. MIT Press.

  • Hinton, G. E. (1989). Connectionist learning procedures,Artificial Intelligence, 40 (1–3).

    Google Scholar 

  • Hinton, G. E. and Anderson, J. A. (1981).Parallel Models of Associative Memory. Lawrence Erlbaum.

  • Hinton, G. E., McClelland, J. L. and Rumelhart, D. E. (1986). Distributed representations. In D. E. Rumelhart and J. L. McClelland (eds.)Parallel Distributed Processing, 1 (3).

  • Marr, D. (1982).Vision. Freeman.

  • McClelland, J. L. and Kawamoto, A. H. (1986). Mechanism of sentence processing: assigning roles to constituents. In D. E. Rumelhart and J. L. McClelland (eds)Parallel Distributed Processing, 2 (19).

  • McCulloch, W. and Pitts, W. (1943). A logical calculus of the ideas immanent in nervous activity,Bulletin of Mathematical Physics, 5.

  • Newell, A. and Simon, H. A. (1972).Human Problem Solving. Prentice-Hall.

  • Nilsson, N. J. (1980).Principles of Artificial Intelligence. Springer-Verlag.

  • Pinker, S. and Prince, A. (1988). On language and connectionism: analysis of a parallel distributed processing model of language acquisition,Cognition, 28 (1–2).

    Google Scholar 

  • Pylyshyn, Z. W. (1984).Computation and Cognition. MIT Press.

  • Rumelhart, D. E., Hinton, G. E. and McClelland, J. L. (1986). A general framework for parallel distributed processing. In D. E. Rumelhart and J. L. McClelland (eds)Parallel Distributed Processing, 1 (2).

  • Rumelhart, D. E. and McClelland, J. L. (eds). (1986).Parallel Distributed Processing. MIT Press.

  • Rumelhart, D. E., Smolensky, P., McClelland, J. K. and Hinton, G. E. (1986). Schemata and sequential thought processes in PDP models. In D. E. Rumelhart and J. L. McClelland (eds)Parallel Distributed Processing, 2 (14).

  • Smolensky, P. (1987). On variable binding and the representation of symbolic structures in connectionist systems. University of Colorado Technical Report CU-CS 355-87.

  • Smolensky, P. (1987). On the proper treatment of connectionism,Behavioral and Brain Sciences, 11 (1).

  • Touretzky, D. S. and Hinton, G. E. (1985). Symbols among the neurons: details of a connectionist inference architecture,Proc. IJCAI, 85.

  • Touretzky, D. S. and Hinton, G. E. (1988). A distributed connectionist production system,Cognitive Science, 12.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Memmi, D. Connectionism and artificial intelligence as cognitive models. AI & Soc 4, 115–136 (1990). https://doi.org/10.1007/BF01889639

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01889639

Keywords

Navigation