TL;DR: Graphical modeling using L-systems and turtle interpretation of symbols for plant models and iterated function systems, and Fractal properties of plants.
Abstract: 1 Graphical modeling using L-systems.- 1.1 Rewriting systems.- 1.2 DOL-systems.- 1.3 Turtle interpretation of strings.- 1.4 Synthesis of DOL-systems.- 1.4.1 Edge rewriting.- 1.4.2 Node rewriting.- 1.4.3 Relationship between edge and node rewriting.- 1.5 Modeling in three dimensions.- 1.6 Branching structures.- 1.6.1 Axial trees.- 1.6.2 Tree OL-systems.- 1.6.3 Bracketed OL-systems.- 1.7 Stochastic L-systems.- 1.8 Context-sensitive L-systems.- 1.9 Growth functions.- 1.10 Parametric L-systems.- 1.10.1 Parametric OL-systems.- 1.10.2 Parametric 2L-systems.- 1.10.3 Turtle interpretation of parametric words.- 2 Modeling of trees.- 3 Developmental models of herbaceous plants.- 3.1 Levels of model specification.- 3.1.1 Partial L-systems.- 3.1.2 Control mechanisms in plants.- 3.1.3 Complete models.- 3.2 Branching patterns.- 3.3 Models of inflorescences.- 3.3.1 Monopodial inflorescences.- 3.3.2 Sympodial inflorescences.- 3.3.3 Polypodial inflorescences.- 3.3.4 Modified racemes.- 4 Phyllotaxis.- 4.1 The planar model.- 4.2 The cylindrical model.- 5 Models of plant organs.- 5.1 Predefined surfaces.- 5.2 Developmental surface models.- 5.3 Models of compound leaves.- 6 Animation of plant development.- 6.1 Timed DOL-systems.- 6.2 Selection of growth functions.- 6.2.1 Development of nonbranching filaments.- 6.2.2 Development of branching structures.- 7 Modeling of cellular layers.- 7.1 Map L-systems.- 7.2 Graphical interpretation of maps.- 7.3 Microsorium linguaeforme.- 7.4 Dryopteris thelypteris.- 7.5 Modeling spherical cell layers.- 7.6 Modeling 3D cellular structures.- 8 Fractal properties of plants.- 8.1 Symmetry and self-similarity.- 8.2 Plant models and iterated function systems.- Epilogue.- Appendix A Software environment for plant modeling.- A.1 A virtual laboratory in botany.- A.2 List of laboratory programs.- Appendix B About the figures.- Turtle interpretation of symbols.
TL;DR: Growth functions of informationless Lindenmayer systems are investigated from the point of view of integral sequential word functions and some of the inclusion relations between language families do not remain valid for the corresponding families of growth functions.
Abstract: Growth functions of informationless Lindenmayer systems are investigated from the point of view of integral sequential word functions. Algorithms are obtained for the solution of equivalence, minimization and construction problems. It is found out that some of the inclusion relations between language families do not remain valid for the corresponding families of growth functions. Some results concerning context-dependent Lindenmayer systems, as well as growth relations of OL-systems are also obtained.
TL;DR: This work summarizes recurrent iterated function systems and L-systems, and provides methods with examples for converting such models to the object instancing paradigm, allowing it to model linear fractals.
Abstract: The recurrent iterated function system and the L-system are two powerful linear fractal models. The main drawback of recurrent iterated function systems is a difficulty in modeling whereas the main drawback of L-systems is inefficient geometry specification. Iterative and recursive structures extend the object instancing paradigm, allowing it to model linear fractals. Instancing models render faster and are more intuitive to the computer graphics community. A preliminary section briefly introduces the object instancing paradigm and illustrates its ability to model linear fractals. Two main sections summarize recurrent iterated function systems and L-systems, and provide methods with examples for converting such models to the object instancing paradigm. Finally, a short epilogue describes a particular use of color in the instancing paradigm and the conclusion outlines directions for further research.
TL;DR: The ideas behind grammar evolution are used to automatically generate and evolve Lindenmayer grammars which represent fractal curves with a fractal dimension that approximates a predefined required value.
Abstract: Lindenmayer grammars have frequently been applied to represent fractal curves. In this work, the ideas behind grammar evolution are used to automatically generate and evolve Lindenmayer grammars which represent fractal curves with a fractal dimension that approximates a predefined required value. For many dimensions, this is a nontrivial task to be performed manually. The procedure we propose closely parallels biological evolution because it acts through three different levels: a genotype (a vector of integers), a protein-like intermediate level (the Lindenmayer grammar), and a phenotype (the fractal curve). Variation acts at the genotype level, while selection is performed at the phenotype level (by comparing the dimensions of the fractal curves to the desired value).
TL;DR: The notion of a K-iteration grammar, where K is a family of languages, provides a uniform framework for discussing the various language families obtained by context-free Lindenmayer systems as mentioned in this paper.
Abstract: The notion of a K-iteration grammar, where K is a family of languages, provides a uniform framework for discussing the various language families obtained by context-free Lindenmayer systems. It is shown that the family of languages generated by K-iteration grammars possesses strong closure properties under the assumption that K itself has certain weak closure properties. Along these lines, the notion of a hyper-AFL is introduced and some open problems are posed.