Abstract

Agent-based modeling and simulation (ABMS) is an approach for exploring the behaviors and interactions of individuals or organizations in particular situations or environments. Individuals can be any entity that behaves somewhat autono-mously and interacts with other agents, e.g. humans, animals, bacteria, blood cells or molecules. Organizations can be any collection of entities whose behavior can be characterized as the behavior of a group. Examples might be sports teams, project teams, political organizations, terrorist organizations, legislatures, military organizations, or towns. An ABMS may be used to model a system and answer questions about that system, or predict the ways that the system will respond to external influences. The system being modeled may be an existing system, which is being analyzed to understand the behavior in response to specific changes in the environment, or a new system being designed or built. This chapter will give an overview of ABMS, discuss agent characteristics and frameworks, and use an example to describe how to create an ABMS.

Keywords

Defend 

References

  1. Brenner W, Zarnekow R, Wittig H (2012) Intelligent software agents: foundations and applications. Springer, New YorkGoogle Scholar
  2. Burkhart R, Langton C, Askenazi M (1996) The swarm simulation system: a toolkit for building multi-agent simulations. Santa Fe Institute, Santa FeGoogle Scholar
  3. Grimm V, Railsback SF (2006) Agent-based models in ecology: patterns and alternative theories of adaptive behaviour. In: Billari FC et al (eds) Agent-based computational modelling. Physica-Verlag HD, Heidelberg, pp 139–152Google Scholar
  4. Grimm V, Railsback SF (2011). Agent-based and individual-based modeling: a practical introduction. Princeton University Press, PrincetonGoogle Scholar
  5. Macal CM, North MJ (2006) Tutorial on agent-based modeling and simulation, Part 2: how to model with agents. In: Perrone LF et al (eds) The 38th conference on winter simulation. Monterey, California, pp 73–83Google Scholar
  6. Macal CM, North MJ (2010) Tutorial on agent-based modelling and simulation. J Simulat 4(3):151–162CrossRefGoogle Scholar
  7. Rao AS, Georgeff MP (1995). BDI agents: from theory to practice. ICMAS 95:312–319Google Scholar
  8. Wilensky U (1999) NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston
  9. Wilensky U (2005) NetLogo user manual version 3.0. 2. Center for Connected Learning and Computer-Based Modeling. Northwestern University, EvanstonGoogle Scholar

Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  1. 1.Georgia Tech Research InstituteAtlantaUSA

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