Abstract
Lindenmayer systems (L-systems) are a formal grammar system that iteratively rewrites all symbols of a string, in parallel. When visualized with a graphical interpretation, the images have been particularly successful as a concise method for simulating plants. Creating L-systems to simulate a given plant manually by experts is limited by the availability of experts and time. This paper introduces the Plant Model Inference Tool (PMIT) that infers deterministic context-free L-systems from an initial sequence of strings generated by the system using a genetic algorithm. PMIT is able to infer more complex systems than existing approaches. Indeed, while existing approaches can infer D0L-Systems where the sum of production successors is 20, PMIT can infer those where the sum is 140. This was validated using a testbed of 28 known D0L-system models, in addition to models created artificially by bootstrapping larger models.
This research was supported in part by a grant from the Plant Phenotyping and Imaging Research Centre.
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Bernard, J., McQuillan, I. (2018). New Techniques for Inferring L-systems Using Genetic Algorithm. In: Korošec, P., Melab, N., Talbi, EG. (eds) Bioinspired Optimization Methods and Their Applications. BIOMA 2018. Lecture Notes in Computer Science(), vol 10835. Springer, Cham. https://doi.org/10.1007/978-3-319-91641-5_2
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