GAIG Game AI Research Group @ QMUL

The importance of applying computational creativity to scientific and mathematical domains

2019
Pease, Alison and Colton, Simon and Warburton, Chris and Nathanail, Athanasios and Preda, Irina and Arnold, Daniel and Winterstein, Daniel and Cook, Mike

Abstract

Science and mathematics are currently underrepresented in the computational creativity (CC) community. We discuss why the CC community should apply their work to mathematical and scientific domains, and argue that this would be mutually beneficial for the domains in question. We identify a key challenge in Automated Reasoning – that it has not achieved widespread adoption by mathematicians; and one in Automated Scientific Discovery – the need for communicability of automatically generated scientific knowledge. We recommend that CC researchers help to address these two challenges by: (i) applying systems based on cognitive mechanisms to scientific and mathematical domains; (ii) employing experience in building and evaluating interactive systems to this context; and (iii) using expertise in automatically producing framing functionality to enhance the communicability of automatically generated scientific knowledge.

Cite this work

@inproceedings{pease2019importance,
author= {Pease, Alison and Colton, Simon and Warburton, Chris and Nathanail, Athanasios and Preda, Irina and Arnold, Daniel and Winterstein, Daniel and Cook, Mike},
title= {{The importance of applying computational creativity to scientific and mathematical domains}},
year= {2019},
booktitle= {{10th International Conference on Computational Creativity}},
pages= {250--257},
abstract= {Science and mathematics are currently underrepresented in the computational creativity (CC) community. We discuss why the CC community should apply their work to mathematical and scientific domains, and argue that this would be mutually beneficial for the domains in question. We identify a key challenge in Automated Reasoning – that it has not achieved widespread adoption by mathematicians; and one in Automated Scientific Discovery – the need for communicability of automatically generated scientific knowledge. We recommend that CC researchers help to address these two challenges by: (i) applying systems based on cognitive mechanisms to scientific and mathematical domains; (ii) employing experience in building and evaluating interactive systems to this context; and (iii) using expertise in automatically producing framing functionality to enhance the communicability of automatically generated scientific knowledge.},
}

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