Computational Science Technical Note CSTN-153


Spatial Agent-based Modelling and Simulations - A Review

A. V. Husselmann and K. A. Hawick

Archived April 2012


Agent-based Modelling (ABM) is a powerful technique for studying complex and emergent phenomena in many areas of science, including engineering, sociology, and other fields where collective macroscopic properties are driven by individual microscopic behaviours. Agents are typically modelled as a short set or rules or encoded microscopic behaviours that each agent in a system will use to interact with its environment. Spatial or situated agents are given a location in a simulated space -- typically in 2 or 3 dimensions and thus they have additional ways to interact with their environment. In this article we review some common approaches to modelling spatial agents and identify two main categories of models based on continuous space or discrete-mesh space. We explore two representative models for flocking animats and for mood propagation and use these to discuss how fast and efficient spatial ABMs can be simulated in order to explore multi-scale collective phenomena. We consider data-parallel simulation technologies and approaches such as the use of graphical processing units as accelerators and other computational optimisation ideas.

Keywords: Agent-based models; spatial agents; complex systems; simulation; emergent phenomena.

Full Document Text: PDF version.

Citation Information: BiBTeX database for CSTN Notes.

BiBTeX reference:

  author = {A. V. Husselmann and K. A. Hawick},
  title = {Spatial Agent-based Modelling and Simulations - A Review},
  institution = {Computer Science, Massey University},
  year = {2011},
  number = {CSTN-153},
  address = {Albany, North Shore,102-904, Auckland, New Zealand},
  month = {October},
  note = {In Proc. IIMS Postgraduate Student Conference, October 2011.},
  timestamp = {2012.05.03}

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