Name
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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-319-91641-5_2 | BIOINSPIRED OPTIMIZATION METHODS AND THEIR APPLICATIONS, BIOMA 2018 |
Keywords | DocType | Volume |
L-systems,Inductive inference,Genetic algorithm,Plant modeling | Conference | 10835 |
ISSN | Citations | PageRank |
0302-9743 | 1 | 0.39 |
References | Authors | |
2 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jason Bernard | 1 | 2 | 1.45 |
| Ian McQuillan | 2 | 97 | 24.72 |