Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/12439
Title: Improving the Efficiency of Large-Scale Agent-Based Models Using Compression Techniques
Contributor(s): Welch, Mitchell  (author)orcid ; Kwan, Paul H  (author); Sajeev, Abudulkadir  (author); Garner, Graeme (author)
Publication Date: 2012
DOI: 10.4018/978-1-4666-1830-5.ch018
Handle Link: https://hdl.handle.net/1959.11/12439
Abstract: Agent-based modelling is becoming a widely used approach for simulating complex phenomena. By making use of emergent behaviour, agent based models can simulate systems right down to the most minute interactions that affect a system's behaviour. In order to capture the level of detail desired by users, many agent based models now contain hundreds of thousands and even millions of interacting agents. The scale of these models makes them computationally expensive to operate in terms of memory and CPU time, limiting their practicality and use. This chapter details the techniques for applying Dynamic Hierarchical Agent Compression to agent based modelling systems, with the aim of reducing the amount of memory and number of CPU cycles required to manage a set of agents within a model. The scheme outlined extracts the state data stored within a model's agents and takes advantage of redundancy in this data to reduce the memory required to represent this information. The techniques show how a hierarchical data structure can be used to achieve compression of this data and the techniques for implementing this type of structure within an existing modelling system. The chapter includes a case study that outlines the practical considerations related to the application of this scheme to Australia's National Model for Emerging Livestock Disease Threats that is currently being developed.
Publication Type: Book Chapter
Source of Publication: Multidisciplinary Computational Intelligence Techniques: Applications in Business, Engineering and Medicine, p. 301-326
Publisher: Information Science Reference
Place of Publication: Hershey, United States of America
ISBN: 9781466618305
9781466618312
9781466618329
Field of Research (FOR): 070704 Veterinary Epidemiology
080110 Simulation and Modelling
080102 Artificial Life
Socio-Economic Outcome Codes: 890201 Application Software Packages (excl. Computer Games)
970107 Expanding Knowledge in the Agricultural and Veterinary Sciences
970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Category Description: B1 Chapter in a Scholarly Book
Other Links: http://trove.nla.gov.au/work/163586506
Series Name: Premier Reference Source
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Appears in Collections:Book Chapter

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