Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Handbook of graph grammars and computing by graph transformation: vol. 3: concurrency, parallelism, and distribution
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
A new kind of science
Introduction to Multiagent Systems
Introduction to Multiagent Systems
Molecular Modeling and Simulation: An Interdisciplinary Guide
Molecular Modeling and Simulation: An Interdisciplinary Guide
Self-Organization in Biological Systems
Self-Organization in Biological Systems
Theoretical Computer Science - Natural computing
Data Structure as Topological Spaces
UMC '02 Proceedings of the Third International Conference on Unconventional Models of Computation
An introduction to parallel map generating systems
Proceedings of the 3rd International Workshop on Graph-Grammars and Their Application to Computer Science
Evolutionary On-line Learning of Cooperative Behavior with Situation-Action-Pairs
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
A graph grammar approach to artificial life
Artificial Life
Biomolecular swarms—an agent-based model of the lactose operon
Natural Computing: an international journal
Theory of Self-Reproducing Automata
Theory of Self-Reproducing Automata
Applications of Graph Transformations with Industrial Relevance
Research frontier: the evolution of swarm grammars-growing trees, crafting art, and bottom-up design
IEEE Computational Intelligence Magazine
The swarming body: simulating the decentralized defenses of immunity
ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
ICALP'12 Proceedings of the 39th international colloquium conference on Automata, Languages, and Programming - Volume Part II
Information and Computation
| Hi-index | 0.00 |
Modelling natural processes requires the implementation of an expressive representation of the involved entities and their interactions. We present swarm graph grammars (SGGs) as a bio-inspired modelling framework that integrates aspects of formal grammars, graph-based representation and multi-agent simulation. In SGGs, the substitution of subgraphs that represent locally defined agent interactions drive the computational process of the simulation. The generative character of formal grammars is translated into an agent's metabolic interactions, i.e. creating or removing agents from the system. Utilizing graphs to describe interactions and relationships between pairs or sets of agents offers an easily accessible way of modelling biological phenomena. Property graphs emerge through the application of local interaction rules; we use these graphs to capture various aspects of the interaction dynamics at any given step of a simulation.