Abstract
In this paper we propose a heuristic algorithm for construction an optimal spring network architecture aimed at obtaining desired mechanical behaviour in response to physical input (control) stimuli. The part of the algorithm that searches for a network structure is based on random graph walks. To ensure desired mechanical behaviour of the graph, physical parameters of the spring network are adjusted by an appropriate gradient descent learning algorithm. In addition, we discuss numerical results of the network search procedure.
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Czoków, M., Schreiber, T. (2012). Structure Searching for Adaptive Spring Networks for Shape Programming in 3D . In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7268. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29350-4_25
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DOI: https://doi.org/10.1007/978-3-642-29350-4_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29349-8
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