When physical systems realize functions
Minds and Machines 9 (2):161-196 (1999)
| Abstract | After briefly discussing the relevance of the notions computation and implementation for cognitive science, I summarize some of the problems that have been found in their most common interpretations. In particular, I argue that standard notions of computation together with a state-to-state correspondence view of implementation cannot overcome difficulties posed by Putnam's Realization Theorem and that, therefore, a different approach to implementation is required. The notion realization of a function, developed out of physical theories, is then introduced as a replacement for the notional pair computation-implementation. After gradual refinement, taking practical constraints into account, this notion gives rise to the notion digital system which singles out physical systems that could be actually used, and possibly even built | |||||||||
| Keywords | Artificial Intelligence Computation Computer Physical Science | |||||||||
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David J. Chalmers (2011). A Computational Foundation for the Study of Cognition. Journal of Cognitive Science 12 (4):323-357.
Ronald L. Chrisley (1994). Why Everything Doesn't Realize Every Computation. Minds and Machines 4 (4):403-20.
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Matthias Scheutz (2001). Computational Vs. Causal Complexity. Minds And Machines 11 (4):543-566.
Nir Fresco (2011). Concrete Digital Computation: What Does It Take for a Physical System to Compute? Journal of Logic, Language and Information 20 (4):513-537.
David J. Chalmers (1994). On Implementing a Computation. Minds and Machines 4 (4):391-402.
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