Abstract
L-system is a bio-inspired computational model to capture growth process of plants. This paper proposes a new noise-tolerant grammatical induction LGIC2 for deterministic context-free L-systems. LGIC2 induces L-system grammars from a transmuted string mY, employing an emergent approach in order to enforce its noise tolerance. In the method, frequently appearing substrings are extracted from mY to form grammar candidates. A grammar candidate is used to generate a string Z; however, the number of grammar candidates gets huge, meaning enormous computational cost. Thus, how to prune grammar candidates is vital here. We introduce a couple of techniques such as pruning by frequency, pruning by goodness of fit, and pruning by contractive embedding. Finally, several candidates having the strongest similarities between mY and Z are selected as the final solutions. Our experiments using insertion-type transmutation showed that LGIC2 worked very nicely, much better than an enumerative method LGIC1.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Cormen, T.H., Leiserson, C.E., Rivest, R.L.: Introduction to algorithms. MIT Press (1990)
Damasevicius, R.: Structural analysis of regulatory DNA sequences using grammar inference and support vector machine. Neurocomputing 73, 633–638 (2010)
de la Higuera, C.: A bibliographical study of grammatical inference. Pattern Recognition 38, 1332–1348 (2005)
Hjaltason, G.R., Samet, H.: Contractive embedding methods for similarity searching in metric spaces. Technical Report CS-TR-4102, Univ. of Maryland (2000)
Levenshtein, V.: Binary codes capable of correcting deletions, insertions, and reversals. Soviet Physics Doklady 10(8), 707–710 (1966)
McCormack, J.: Interactive evolution of L-system grammars for computer graphics modelling. In: Complex Systems: From Biology to Computation, pp. 118–130. ISO Press, Amsterdam (1993)
Nakano, R.: Error correction of enumerative induction of deterministic context-free L-system grammar. IAENG Int. Journal of Computer Science 40(1), 47–52 (2013)
Nakano, R., Suzumura, S.: Grammatical induction with error correction for deterministic context-free L-systems. In: Proc. of the World Congress on Engineering and Computer Science 2012 (WCECS 2012), pp. 534–538 (2012)
Nakano, R., Yamada, N.: Number theory-based induction of deterministic context-free L-system grammar. In: Proc. Int. Joint Conf. on Knowledge Discovery, Knowledge Engineering and Knowledge Management 2010, pp. 194–199 (2010)
Nevill-Manning, C.G.: Inferring sequential structure. Technical Report Doctoral Thesis, Univ. of Waikato (1996)
Prusinkiewicz, P., Hanan, J.: Lindenmayer systems, fractals, and plants. Springer, New York (1989)
Prusinkiewicz, P., Lindenmayer, A.: The algorithmic beauty of plants. Springer, New York (1990)
Schlecht, J., Barnard, K., Springgs, E., Pryor, B.: Inferring grammar-based structure models from 3d microscopy data. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Nakano, R. (2014). Emergent Induction of Deterministic Context-Free L-system Grammar. In: Abraham, A., Krömer, P., Snášel, V. (eds) Innovations in Bio-inspired Computing and Applications. Advances in Intelligent Systems and Computing, vol 237. Springer, Cham. https://doi.org/10.1007/978-3-319-01781-5_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-01781-5_7
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01780-8
Online ISBN: 978-3-319-01781-5
eBook Packages: EngineeringEngineering (R0)