Computational Scientific Discovery and Cognitive Science Theories

Addis, Mark and Sozou, Peter D and Lane, Peter C and Gobet, Fernand (2016) Computational Scientific Discovery and Cognitive Science Theories. In: Computing and Philosophy: Proceedings of IACAP 2014. Synthese Library (375). Springer, Heidelberg, 83 -97. ISBN 978-3-319-23290-4

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This study is concerned with processes for discovering new theories in science. It considers a computational approach to scientific discovery, as applied to the discovery of theories in cognitive science. The approach combines two ideas. First, a process-based scientific theory can be represented as a computer program. Second, an evolutionary computational method, genetic programming, allows computer programs to be improved through a process of computational trial-and-error. Putting these two ideas together leads to a system that can automatically generate and improve scientific theories. The application of this method to the discovery of theories in cognitive science is examined. Theories are built up from primitive operators. These are contained in a theory language that defines the space of possible theories. An example of a theory generated by this method is described. These results support the idea that scientific discovery can be achieved through a heuristic search process, even for theories involving a sequence of steps. However, this computational approach to scientific discovery does not eliminate the need for human input. Human judgment is needed to make reasonable prior assumptions about the characteristics of operators used in the theory generation process, and to interpret and provide context for the computationally generated theories.

Item Type: Book Section
Subjects: 100 Philosophy & psychology > 121 Epistemology
School/Department: School of Arts and Humanities
Depositing User: Mark Addis
Date Deposited: 28 Jun 2017 08:34
Last Modified: 28 Jun 2017 08:34


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