# Information Processing as an Account of Concrete Digital Computation

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## Abstract

It is common in cognitive science to equate computation (and in particular digital computation) with information processing. Yet, it is hard to find a comprehensive explicit account of concrete digital computation in information processing terms. An information processing account seems like a natural candidate to explain digital computation. But when ‘information’ comes under scrutiny, this account becomes a less obvious candidate. Four interpretations of information are examined here as the basis for an *information processing* account of digital computation, namely Shannon information, algorithmic information, factual information and instructional information. I argue that any plausible account of concrete computation has to be capable of explaining at least the three key algorithmic notions of input, output and procedures. Whist algorithmic information fares better than Shannon information, the most plausible candidate for an information processing account is instructional information.

## Keywords

Concrete digital computation Turing machines Algorithmic information Shannon information Factual information Instructional information Cognitive science Algorithm Program## Notes

### Acknowledgements

Part of this research was done during a visiting fellowship at the IAS-STS in Graz, Austria in 2011. Thanks to Gualtiero Piccinini, Oron Shagrir and Matt Johnson for useful comments on earlier drafts of this paper. I have greatly benefited from discussions with Naftali Tishby and Karl Posch on the mathematical theory of information and with Cristian Calude on algorithmic information theory and for that I am grateful. I would also like to express my gratitude to both Graham White and Marty Wolf, who refereed the paper and agreed to drop their anonymity in the process. Their insightful comments helped reshape and improve this paper significantly. I am indebted to Phillip Staines for his detailed comments and ongoing support. Earlier versions of this paper were presented at the 2010 AAPNZ conference in Hamilton, NZ, the 2011 AISB convention in York, UK and the IAS-STS fellowship colloquium in Graz, Austria. All the people mentioned above contributed to the final draft of the paper, but I am responsible for any remaining mistakes. This paper is dedicated in loving memory of Moshe Bensal.

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