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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/2088

Title: A methodology for developing computational implementations of scientific theories
Authors: Lane, PCR
Gobet, F
Keywords: Scientific theory
Methodology
Computational modeling
Quantitative prediction
Unified theory of cognition
Newell
Agile computational modeling
Cognitive architecture
Cognitive science
Soar
ACT-R
Scientific-testing methodology
Implementation
Model
XP
Agile programming
Test-driven development
Canonical results
Process test
Unit test
Optimization
Non-dominated sorting genetic algorithm
Speciated-NDSGA
NDSGA
Lakatos
Genetic algorithm
Publication Date: 2008
Publisher: IEEE
Citation: Proceedings of the 10th International Conference on Computer Modelling and Simulation. Institute of Electrical and Electronics Engineers.
Abstract: Computer programs have become a popular representation for scientific theories, particularly for implementing models or simulations of observed phenomena. Expressing a theory as an executable computer program provides many benefits, including: making all processes concrete, supporting the development of specific models, and hence enabling quantitative predictions to be derived from the theory. However, as implementations of scientific theories, these computer programs will be subject to change and modification. As programs change, their behaviour will also change, and ensuring continuity in the scientific value of the program is difficult. We propose a methodology for developing computer software implementing scientific theories. This methodology allows the developer to continuously change and extend their software, whilst alerting the developer to any changes in its scientific interpretation. We introduce tools for managing this development process, as well as for optimising the developed models.
URI: http://bura.brunel.ac.uk/handle/2438/2088
Appears in Collections:School of Social Sciences Research Papers
Psychology

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