Result: Relational growth grammars : A graph rewriting approach to dynamical systems with a dynamical structure

Title:
Relational growth grammars : A graph rewriting approach to dynamical systems with a dynamical structure
Source:
UPP 2004 : unconventional programming paradigms (15-17 September 2004, Mont Saint Michel, revised selected & invited papers)Lecture notes in computer science. :56-72
Publisher Information:
Berlin: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 20 ref
Original Material:
INIST-CNRS
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Brandenburgische Technische Universität Cottbus, Department of Computer Science, Chair for Practical Computer Science/Graphics Systems, P.O.Box 101344, 03013 Cottbus, Germany
Institute of Plant Genetics and Crop Plant Research (IPK), Dept. Cytogenetics, Corrensstr. 3, 06466 Gatersleben, Germany
ISSN:
0302-9743
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.17134547
Database:
PASCAL Archive

Further Information

Relational growth grammars (RGG) are a graph rewriting formalism which extends the notations and semantics of Lindenmayer systems and which allows the specification of dynamical processes on dynamical structures, particularly in biological and chemical applications. RGG were embedded in the language XL, combining rule-based and conventional object-oriented constructions. Key features of RGG and of the software GroIMP (Growth grammar related Interactive Modelling Platform) are listed. Five simple examples are shown which demonstrate the essential ideas and possibilities of RGG: signal propagation in a network, cellular automata, globally-sensitive growth of a plant, a chemical prime number generator, and a polymerisation model using a simple mass-spring kinetics.