Concepts of computations in modern theories of human cognition
https://doi.org/10.17726/philIT.2018.1.1
Abstract
As the history of cognitive science testifies, most of the problems and corresponding discussions are built around two basic concepts: representations and computations. The known schools, or ‘paradigms’, of cognitive disciplines differ depending on their adopting or denouncing the relevance of these concepts for their theories, as well as on a certain understanding of the nature of phenomena referred thereby. Since representations, if adopted and allowed, are considered a necessary element of computational processes, then we are not mistaken if we say that the entire spectrum of cognitive theories is aligned with the basic concept of computation - from accepting them in the strictest (formal-symbolic, Turing-style) versions, through more ‘weak’ non-Turing concepts, to a complete denial of the applicability of this concept to the sphere of cognition and conscious control. Below, I will try to analyze the current approaches in cognitive science with a view to classifying them as a strong or weak version of computationalism - or as a radical anti-computationalism
References
1. Fodor, J. A., Pylyshyn, Z. W. Connectionism and cognitive architecture: A critical analysis. Cognition, No. 28, 1988. p. 3-71
2. Smolensky P. On the Proper Treatment of Connectionism. Behavioral and Brain Sciences. No. 11, 1988. p. 1-74
3. Ramsey W. Do Connectionist Representations Earn their Explanatory Keep? Mind & Language, Vol. 12. No. I, 1997. p. 34-66
4. Thelen E., Bates E. Connectionism and dynamic systems: are they really different? Developmental Science Vol. 6, No. 4, 2003. p. 378-391
5. O’Brien G., Opie J. Radical connectionism: thinking with (not in) language. Language & Communication, Volume 22, Issue 3, July 2002, 313-329
6. Hutto D. D. Representation Reconsidered. Philosophical Psychology, Vol. 24, No. 1, 2011 p. 135-139. DOI: 10.1080/09515089.2010.529261
7. Hutto D. D., Myin E. Radicalizing enactivism: basic minds without content. Cambridge, MIT Press, 2013. 206 p.
8. Smith L. B., Thelen, E. Development as a dynamic system. Trends in Cognitive Sciences. Vol. 7, No. 8, 2003. p. 343-348. DOI: 10.1016/S 1364- 6613(03)00156-6
9. Hohwy J. The Predictive Mind. Oxford, 2013. 282 p
10. Gärtner K., Clowes R. W. Enactivism, Radical Enactivism and Predictive Processing: What is Radical in Cognitive Science? Kairos. Journal of Philosophy & Science, No. 18, 2017
11. Aderson J. R. The architecture of cognition. Cambridge, Massachusetts: Harvard University Press, 1983. 340 p.
12. Fresco N. The Explanatory Role of Computation in Cognitive Science. Minds & Machines No. 22, 2012, p. 353-380. DOI 10.1007/s11023-012- 9286-y
13. Marr D., Poggio T. From Understanding Computation to Understanding Neural Circuitry. Neurosciences Research Program Bulletin , Vol. 15, No.3, 1979. p. 470-488
14. Marr D. Vision: a computational investigation into the human representation and processing of visual information. Cambridge: MIT Press, 2010. 369 p.
15. Poggio T. The Levels of Understanding framework, revised. Perception, Vol. 41, 2012. p. 1017-1023. doi: 10.1068/p7299
16. Craver C. F., Bechtel, W. Mechanism. In: S. Sarkar, J. Pfeifer (Eds.), Philosophy of science: An encyclopedia. New York: Routledge, 2006, pp. 469-478
17. Goldstein L., Slater H. Wittgenstein, Semantics and Connectionism. Philosophical Investigations, Volume 21, Issue 4, 1998. p. 293-314
18. Kempes C. P.; Wolpert D.; Cohen Z.; Pérez-Mercader J. The thermodynamic efficiency of computations made in cells across the range of life. Phil. Trans. R. Soc. A 375: 20160343, 2017. http://dx.doi. org/10.1098/rsta.2016.0343
19. Flack J. C. Coarse-graining as a downward causation mechanism. In: Phil. Trans. R. Soc. A 375: 20160338, 2017. http://dx.doi.org/10.1098/ rsta.2016.0338
20. Marshall W., Albantakis L., Tononi G. Black-boxing and cause-effect power. PLoS Comput Biol, Vol. 14, No. 4: e1006114, 2018. https://doi. org/10.1371/journal.pcbi.1006114
Review
For citations:
Mikhailov I.F. Concepts of computations in modern theories of human cognition. Philosophical Problems of IT & Cyberspace (PhilIT&C). 2018;(1):4-21. (In Russ.) https://doi.org/10.17726/philIT.2018.1.1
Views:
180
Email this article 