Connectionism, Artificial Life, and Dynamical Systems

A Companion to Cognitive Science

Volumn , Issue , 2008, Pages 488-505

  Elman, Jeffrey L ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Artificial life; Cognition as a dynamical system; Historical context; Issues and controversies

Indexed keywords

EID: 85052774542     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9781405164535.ch38     Document Type: Chapter

References (17)

1. Bechtel, W. and Abrahamsen, A. 1991: Connectionism and the Mind: An Introduction to Parallel Processing in Networks. Cambridge, Mass.: Basil Blackwell.
2. Brakenberg, V. 1984: Vehicles: Experiments in Synthetic Psychology. Cambridge, Mass.: MIT Press.
3. Elman, J. L. 1990: Finding structure in time. Cognitive Science, 14, 179-211.
4. Elman, J. L. 1991: Distributed representations, simple recurrent networks, and grammatical structure. Machine Learning, 7, 195-225.
5. Fodor, J. A. and Pylyshyn, Z. W. 1988: Connectionism and cognitive architecture: a critical analysis. In S. Pinker and J. Mehler (eds), Connections and Symbols, Cambridge, Mass.: MIT Press, 3-71.
6. Hinton, G. E. and Anderson, J. A. 1981: Parallel Models of Associative Memory. Hillsdale, NJ: Erlbaum.
7. Holland, J. H. 1975: Adaptation in Natural and Artificial Systems. Ann Arbor: University of Michigan Press.
8. Langton, C. G. 1989: Artificial Life, Santa Fe Institute Studies in the Sciences of Complexity Proceedings, vol. 6. Redwood City, Calif.: Addison-Wesley.
9. McClelland, J. L. and Rumelhart, D. E. 1981: An interactive activation model of context effects in letter perception: part 1. An account of the basic findings. Psychological Review, 86, 287-330.
10. McClelland, J. L., Rumelhart, D. E. and the PDP Research Group 1986: Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 2: Psychological and Biological Models. Cambridge, Mass.: MIT Press.
11. Nolfl, S., Elman, J. L. and Parisi, D. 1994: Learning and evolution in neural networks. Adaptive Behavior, 3, 5-28.
12. Pinker, S. and Prince, A. 1988: On language and connectionism: analysis of a parallel distributed processing model of language acquisition. Cognition, 28, 73-193.
13. Port, R. and van Gelder, T. 1995: Mind as Motion: Dynamical Perspectives on Behavior and Cognition. Cambridge, Mass.: MIT Press.
14. Rumelhart, D. E. and McClelland, J. L. 1986: On learning the past tenses of English verbs. In D. E. Rumelhart and J. L. McClelland (eds), Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 2: Psychological and Biological Models, Cambridge, Mass.: MIT Press, 216-71.
15. Rumelhart, D. R, McClelland, J. L. and the PDP Research Group 1986: Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 1: Foundations. Cambridge, Mass.: MIT Press.
16. Servan-Schreiber, D., Cleeremans, A. and McClelland, J. L. 1991: Graded state machines: the representation of temporal contingencies in simple recurrent networks. Machine Learning, 7, 161-93.
17. Wiles, J., Rodriguez, P. and Elman, J. L. 1995: Learning to count without a counter: a case study of dynamics and activation landscapes in recurrent networks. In Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society, Hillsdale, NJ: Erlbaum, 482-7.