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Modeling and Simulation of Complex Systems: A Framework for Efficient Agent-Based Modeling and Simulation

Siegfried, Robert
Springer-Verlag: Berlin, 2014
ISBN 978-3658075286 (pb)

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Reviewed by Andreas Koch
University of Salzburg

Cover of book The intention of Modeling and Simulation of Complex Systems by Robert Siegfried is to provide a framework for efficient agent-based modelling and simulation as the subtitle of the book suggests. There are two main goals that have been outlined in the work written as a PhD thesis: “providing a solid foundation of agent-based modelling and simulation” and “enabling small-scale development and smooth transition to large-scale models” (p. 6). The core concept to achieve these goals is a General Reference Model for Agent-Based Modeling and Simulation (GRAMS), which consists of two components, one that is provided for the definition of basic building blocks and a second that serves as a toolbox for the definition of constraints for the simulation of a model.

The book is structured into five parts. While the first part is about “preliminaries and related work”, introducing into agent-based modelling and simulation, and parallel and distributed simulation techniques, the second part presents the GRAMS approach and its justification. Part III deals with the increasing need of applying model partitioning and multi-level parallelisation techniques in order to cope with the growing demand of computing capacity to adequately represent and model complex systems. In addition, it presents exemplary implementations of the GRAMS approach. Chapter IV gives some concluding remarks and Chapter V additional information about two examples outlined before (which is a warehouse and a fire support case study).

Compared with articles of Polhill (2010), Polhill et al. (2008), and Grimm and Railsback (2012) about the ODD protocol concept (Overview, Design Concept, Details) or Isaac (2011) about ABM template model approaches the GRAMS approach does not offer a remarkable novel or different perspective on the problem of how to standardise models and simulations in a comprehensive and thorough way. In fact, Siegfried fails to include current introductions of existing software approaches and tools that have been developed so far (see, for example, Crooks and Heppenstall (2012)) and that also struggle with the problem of reference models and a paradigmatic ontology. His GRAMS approach focuses, within the entire chain of the model development process, exclusively on the conceptual and formal model step in order to support system analysis and formalisation.

More valuable are his reflections on the partitioning and parallelisation problem. Here he distinguishes between “partitioning at the macro-level” (environment) and “partitioning at the micro-level” (agent), and between static and dynamic partitioning. The aim is to increase the computational effectivity in order to approach complex systems in a modelling environment as close as possible. Siegfried argues that “the most challenging aspect when considering parallel execution is the decomposition of an agent-based model into the required number of independent partitions”, and his strategy is to rearrange existing partitioning approaches within a common framework. While the technological approach appears to be convincing it still (at least to some extent) remains an existing epistemological challenge of how to discriminate a complex system properly into coherent subparts, i.e. preserving the complexity property and decomposing the system.

In this respect the book is worth reading by those who are interested in trying to solve theoretical model complexity problems by solving computational constraints.


* References

CROOKS, A. T. and Heppenstall, A. J. (2012), Introduction to Agent-Based Modeling. In: Heppenstall, A. J., Crooks, A. T., See L. M., Batty M. (eds.): Agent-Based Models of Geographical Systems. Dordrecht, Heidelberg, London, New York: Springer, p. 85-106.

GRIMM, V. and Railsback, S. F. (2012), Designing, Formulating, and Communicating Agent-Based Models. In: Heppenstall, A. J., Crooks, A. T., See L. M., Batty M. (eds.): Agent-Based Models of Geographical Systems. Dordrecht, Heidelberg, London, New York: Springer, p. 361-378.

ISAAC, A. G. (2011), The ABM Template Models: A Reformulation with Reference Implementations. Journal of Artificial Societies and Social Simulation, 14 (2) 5, http://jasss.soc.surrey.ac.uk/14/2/5.html

POLHILL, G. (2010), ODD updated. Journal of Artificial Societies and Social Simulation, 13 (4) 9, http://jasss.soc.surrey.ac.uk/13/4/9.html

POLHILL, G., Parker, D., Brown, D., Grimm, V. (2008), Using the ODD Protocol for Describing Three Agent-Based Social Simulation Models of Land-Use Change. Journal of Artificial Societies and Social Simulation, 11 (2) 3, http://jasss.soc.surrey.ac.uk/11/2/3.html

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