Abstract
The properties of engineering structures such as cars, cell phones or bridges rely on materials and on the properties of these materials. The study of these properties, which are determined by the internal architecture of the material or microstructure, has significant importance for material scientists. One of the things needed for this study is a tool that can create microstructural patterns. In this paper we explore the use of a genetic algorithm to evolve the rules of an effector automata to recreate these microstructural patterns.
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References
Gordon G. E. Structures or Why Things Don’t Fall Down, Pelican Books, London. (1978)
Raabe D. Computational Materials Science: The simulation of materials, microstructures and properties, Wiley, Weinheim.. (1998)
Basanta D., Miodownik M. A., Holm E. A., and Bentley P. J. Designing the Internal Architecture of Metals using a Genetic Algorithm. Computer-Based Design. Engineering Design Conference 2002. Professional Engineering Publishing Ltd, London, UK. pp. 349–355. (2002)
Brandon, D., Kaplan, W. D. Microstructural characterization of materials. Wiley, Weinheim, (1999)
Ulam, S. On some mathematical properties connected with patterns of growth of figures. In Proceedings of Symposia on Applied Mathematics, volume 14, pages 215–224. American Mathematical Society. (1962.)
Raabe D. Cellular automata in materials science with particular reference to recrystallization simulation. Annual review of materials research. (2002)
De Garis, H. The Evolutionary Engineering of a Billion Neuron Artificial Brain by 2001 Which Grows/Evolves at Electronic Speeds Inside a Cellular Automata Machine. Published in Sanchez, E., and Tomassini, M. Towards Evolvable Hardware; The Evolutionary Engineering Approach. Springer. (1996)
Mitchell M., Crutchfield J. P., Das R. Evolving Cellular Automata to perform computations. Published in Baeck T., Fogel D., and Michalewicz (Eds.), Handbook of Evolutionary Computation. The institute of physics. (19
Andre, D., Bennett, F., Koza, J. Discovery by genetic programming of a cellular automata rule that is better than any known rule for the majority classification problem. Published in Koza, J. R, Goldberg, D. E., Fogel, D. B., Riolo, R. L., Genetic Programming 1996: Proceedings of the First Annual Conference, MIT Press. (19
Corno, F., Reorda, M. S., and Squillero, G. Exploiting the Selfish Gene Algorithm for Evolving Hardware Cellular Automata. Proceedings of the 2000 Congress on Evolutionary Computation CEC00. IEEE press. (2000).
Kumar, S., Bentley, P. The ABCs of evolutionary design. Investigating the evolvability of embryogenies for morphogenesis. Genetic and Evolutionary Computation Conference (GECCO’ 99) RN/99/2. (1999)
Bentley K. A. (2002). Exploring aesthetic pattern formation. Generative Art 2002 conference proceedings. (2002)
Lohn, J. and Reggia., J. Discovery of Self-Replicating Structures using a Genetic Algorithm. In 1995 IEEE International Conference on Evolutionary Computing. (1995)
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Basanta, D., Bentley, P.J., Miodownik, M.A., Holm, E.A. (2003). Evolving Cellular Automata to Grow Microstructures. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E., Poli, R., Costa, E. (eds) Genetic Programming. EuroGP 2003. Lecture Notes in Computer Science, vol 2610. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36599-0_1
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DOI: https://doi.org/10.1007/3-540-36599-0_1
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