Algorithms for inferring context-sensitive L-systems

Ian McQuillan, Jason Bernard, Przemyslaw Prusinkiewicz

Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

13 Citations (Scopus)

Abstract

Lindenmayer systems (L-systems) are parallel string rewriting systems (grammars). By attaching a graphical interpretation to the symbols in the derived strings, they can be applied to create simulations of temporal processes, and have been especially successful in the modeling of plants. With the objective of automatically inferring L-system models in mind, here we study the inductive inference problem: the inference of models from observed strings. Exact algorithms are given for inferring L-systems that can generate input strings for both deterministic context-free and deterministic context-sensitive L-systems. The algorithms run in polynomial time assuming a fixed number of alphabet symbols and fixed context size. Furthermore, if a specific matrix calculated from the input words is invertible, then a context-sensitive L-system can be automatically created (if it exists) in polynomial time without assuming any fixed parameters.

Original languageEnglish
Title of host publicationUnconventional Computation and Natural Computation - 17th International Conference, UCNC 2018, Proceedings
EditorsSusan Stepney, Sergey Verlan
Pages117-130
Number of pages14
DOIs
Publication statusPublished - 2018
Event17th International Conference on Unconventional Computation and Natural Computation, UCNC 2018 - Fontainebleau, France
Duration: 25 Jun. 201829 Jun. 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10867 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on Unconventional Computation and Natural Computation, UCNC 2018
Country/TerritoryFrance
CityFontainebleau
Period25/06/1829/06/18

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