Can machines think? An old question reformulated
Minds and Machines (forthcoming)
| Abstract | This paper revisits the often debated question Can machines think? It is argued that the usual identification of machines with the notion of algorithm has been both counter-intuitive and counter-productive. This is based on the fact that the notion of algorithm just requires an algorithm to contain a finite but arbitrary number of rules. It is argued that intuitively people tend to think of an algorithm to have a rather limited number of rules. The paper will further propose a modification of the above mentioned explication of the notion of machines by quantifying the length of an algorithm. Based on that it appears possible to reconcile the opposing views on the topic, which people have been arguing about for more than half a century. | |||||||||
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Oron Shagrir (1997). Two Dogmas of Computationalism. Minds and Machines 7 (3):321-44.
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Eli Dresner (2008). Turing-, Human- and Physical Computability: An Unasked Question. Minds and Machines 18 (3).
Kuo-Chin Chang, Tzung-Pei Hong & Shian-Shyong Tseng (1996). Machine Learning by Imitating Human Learning. Minds and Machines 6 (2):203-228.
Paola Cantu' & Italo Testa (2011). Algorithms and Arguments: The Foundational Role of the ATAI-Question. In Frans H. van Eemeren, Bart Garssen, David Godden & Gordon Mitchell (eds.), Proceedings of the Seventh International Conference of the International Society for the Study of Argumentation (pp. 192-203). Rozenberg / Sic Sat.
David A. Nelson (1992). Deductive Program Verification (a Practitioner's Commentary). Minds and Machines 2 (3).
Eric Steinhart (2002). Logically Possible Machines. Minds and Machines 12 (2):259-280.
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