Abstract
Evolutionary algorithms (EAs) have been used in varying ways for design and other creative tasks. One of the main elements of these algorithms is the fitness function used by the algorithm to evaluate the quality of the potential solutions it proposes. The fitness function ultimately represents domain knowledge that serves to bias, constrain, and guide the algorithm’s search for an acceptable solution. In this paper, we explore the degree to which the fitness function’s implementation affects the search process in an evolutionary algorithm. To perform this, the reliability and speed of the algorithm, as well as the quality of the designs produced by it, are measured for different fitness function implementations. These measurements are then compared and contrasted.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bentley, P. (ed.): Evolutionary Design by Computers. Morgan Kaufmann, San Francisco, CA (1999)
Bentley, P., Corne, D.W. (eds.): Creative Evolutionary Systems. Morgan Kaufmann, San Francisco, CA (2002)
Gómez de Silva Garza, A.: Exploring the sensitivity to representation of an evolutionary algorithm for the design of shapes. In: Proceedings of the Eighth ACM International Conference on Creativity and Cognition (C&C’11), pp. 259–267, Atlanta, GA (2011). doi:http://dl.acm.org/citation.cfm?doid=2069618.2069661
Gómez de Silva Garza, A.: The impact of changing the way the fitness function is implemented in an evolutionary algorithm for the design of shapes. In: Proceedings of the Eighth International Conference on Knowledge, Information and Creativity Support Systems (KICSS 2013), pp. 104–113, Krakow, Poland (2013)
Mitchell, M.: An Introduction to Genetic Algorithms. MIT Press, Cambridge, MA (1998)
Acknowledgments
This work has been supported by Asociación Mexicana de Cultura, A.C.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
de Silva Garza, A.G. (2016). Comparing Different Implementations of the Same Fitness Criteria in an Evolutionary Algorithm for the Design of Shapes. In: Skulimowski, A., Kacprzyk, J. (eds) Knowledge, Information and Creativity Support Systems: Recent Trends, Advances and Solutions. Advances in Intelligent Systems and Computing, vol 364. Springer, Cham. https://doi.org/10.1007/978-3-319-19090-7_20
Download citation
DOI: https://doi.org/10.1007/978-3-319-19090-7_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19089-1
Online ISBN: 978-3-319-19090-7
eBook Packages: Computer ScienceComputer Science (R0)