Using Turing Oracles in Cognitive Models
The Process of Programming: Using Turing Oracles in Cognitive Models of Problem-Solving
Jonathan Bartlett (The Blyth Institute)
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At the core of engineering is human problem-solving. Creating a cognitive model of the task of problem-solving is helpful for planning and organizing engineering tasks. One possibility rarely considered in modeling cognitive processes is the use of Turing Oracles (1). Copeland (1998) put forth the possibility of that the mind could make use of Turing Oracles, but never applied that knowledge practically (2). Turing Oracles enable the modeling of processes in the mind which are not computationally-based. Using Turing Oracles may resolve many of the surprising results of computational problem-solving which arise as a result of the Tractable Cognition Thesis (3,4,5). However, as research into the use of Turing Oracles in problem-solving is new, there are many unresolved methodological issues.
(1) Turing, A. M. 1939. Systems of Logic Based on Ordinals. Proceedings of the London Mathematical Society 2:45.
(2) Copeland, B. J. 1998. Turing's O-Machines, Searle, Penrose, and the Brain. Analysis 58(2).
(3) van Rooij. 2008. The Tractable Cognition Thesis. Cognitive Science: A Multidisciplinary Journal 32(6).
(4) Robertson, D.S. 1999. Algorithmic Information Theory, Free Will, and the Turing Test. Complexity 4(3).
MacGregor, J. N., and Y. Chu. 2011. Human Performance on the Traveling Salesman and Related Problems: A Review. The Journal of Problem Solving 3(2).