Technical Report CSI-0031

Detecting Motifs and Lattice Animals in Agent-Based Models on Lattice and Graph Structures

K. A. Hawick

Archived: 2016

Abstract

Motifs or small recurring patterns occur in generalised graphs or networks and can be an indicator and quantitive metric for characterising behaviour in a system. In the special case of graphs that are regular lattices or meshes, the motifs are typically called lattice animals, and are also sometimes used as operator patterns in techniques such as Monte Carlo Renormalisation group calculations. Motifs and lattioce animals can be computed using a number of brute force enumeration techniques but a number of optimised techniques can also be applied to support scaling up to larger patterns. We discuss the scalability and implementation issues of a number of techniques and report on some of the population statistics for some common motif and lattice animal patterns in small random hyper-dimensional agent-based model systems. We discuss how these techniques could be applied to more general graph oriented data structures including those systems stored in graph databases.

Keywords: lattice animal; motif; lattice; graph; hyper-dimension; agent-based model; graph database

Full Document Text: Not yet available.

Citation Information: BiBTeX database for CSI Notes.

BiBTeX reference:

@TechReport{CSI-0031,
        Title = {Detecting Motifs and Lattice Animals in Agent-Based Models on Lattice and Graph Structures},
        Author = {K. A. Hawick},
        Institution = {Computer Science, University of Hull},
        Year = {2016},
        Address = {Cottingham Road, Hull HU6 7RX, UK},
        Month = {April},
        Number = {CSI-0031},
        Type = {CSI},
        Keywords = {lattice animal; motif; lattice; graph; hyper-dimension; agent-based model; graph database},
        Owner = {kahawick},
        Timestamp = {2016.11.13}
}