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by Corry Shores
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[Central Entry Directory]
[Computation Entry Directory]
[Schonbein's Cognition and the Power of Continuous Dynamical Systems, Entry Directory]
[Nick Bostrom & Anders Sandberg argue for digital computation instead of analog for simulating human cognition. They base their contention in part on the "argument from noise." The entries in this series summarize Schonbein's defense of that argument.]
Whit Schonbein
Cognition and the Power
of Continuous Dynamical Systems
5. Conclusion
Schonbein has examined three arguments against analog computation for modelling cognition. The arguments from representation and from measurement were not successful. However, noise is a serious obstacle for the analog argument.
despite there being various abstract automata that possess super-Turing computational power – most notably analog artificial neural networks – their performance under normal circumstances may not exhibit this feature. This detracts from the dynamical systems perspective, since what is lacking from appeals to these sorts of systems is any indication that they are the kinds of things that, when physically realized, retain their additional computational power. (68a)
However, just because analog systems do not have a higher quantity of computational power, they might nonetheless offer something qualitatively different from classical machines, although we do not know yet what that might be.
Dynamical systems such as AANNs, while not offering greater computational power, may nonetheless offer something else – something not provided by classical mechanisms, yet still computational in the traditional sense. Exploring this possibility is left as a future exercise. (68cd)
Schonbein, Whit. "Cognition and the Power of Continuous Dynamical Systems." Mind and Machines, Springer, (2005) 15: pp. 57-71.
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