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From Game Theory to Complexity, Emergence and Agent-Based Modeling in World Politics

  • John A. ParavantisEmail author
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 627)

Abstract

Τhis chapter examines the complexity of world politics with an emphasis on global environmental issues. Concepts of game theory are reviewed and connected to international relations (IR). Game theoretic models found in IR, such as the prisoner’s dilemma, and global environmental negotiations, such as the North-South divide, are presented and discussed. The complexity of world politics, taking place on a highly interconnected global network of actors organized as agents and meta-agents, is presented and discussed as a multiplayer extension of game theory that should not be regarded as a theory alternative to realism but as a novel approach to understanding and anticipating, rather than predicting, global events. Technology, interconnections, feedback and individual empowerment are discussed in the context of the complex world of global politics. Furthermore, evolution and adaptation are related to the concept of fitness and how it may be approached for the case of actors in world politics. Finally, it is suggested that many events of world politics constitute emergent phenomena of the complex international community of state and non-state actors. The presentation is complemented with a review of research problems from the fields of social science, political science, defense, world politics and the global environment that have been successfully addressed with agent-based simulation, arguably the most prevalent method of simulating complex systems. This chapter concludes with a recapping of the main points presented, some suggestions and caveats for future directions as well as a list of software resources useful to those who wish to address global problems with agent-based models.

Keywords

European Union Game Theory Complex Adaptive System North American Free Trade Agreement World Politics 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The author thanks Dr. T. Nadasdi and Dr. S. Sinclair for their online Spell Check Plus (http://spellcheckplus.com) that was used for proofing the entire document.

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List of Software Resources

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  2. 1. Axelrod’s dated but still excellent “Resources for Agent-Based Modeling” may be found as Appendix B in his “Complexity of Cooperation” book (1997). In particular, I strongly concur with his recommendation that a beginner use a procedural language (like BASIC or Pascal) to start working on developing an agent-based modelGoogle Scholar
  3. 2. Axelrod and Tesfatsion’s outstanding online guide, http://www2.econ.iastate.edu/tesfatsi/abmread.htm. Last updated on 28 March 2015
  4. 3. An excellent introductory to the Repast software as well as agent-based models is maintained by Tesfatsion at http://www2.econ.iastate.edu/tesfatsi/repastsg.htm. Last updated on 28 Mar 2015
  5. 4. A thorough list of software resources is presented and commented online by Allan (2011)Google Scholar
  6. 5. Another list of software resources is given by Railsback et al. (2006)Google Scholar
  7. 6. A list of ABM platforms in the CoMSES Network, https://www.openabm.org/page/modeling-platforms
  8. 7. The following ABM systems (with an emphasis on open source and free packages) are suggested for social science simulation by the author of this chapter (in order of personal preference)Google Scholar
  9. 8. Netlogo, https://ccl.northwestern.edu/netlogo, that has inspired a few other tools that are based on it, such as AgentScript (http://agentscript.org) and Modelling4All (http://m.modelling4all.org)
  10. 10. Anylogic, which has a free edition for academic and personal use (Anylogic PLE), http://www.anylogic.com/blog?page=postandid=237
  11. 11. Repast, which offers the capability of being programmed in Java, Relogo or Python http://repast.sourceforge.net
  12. 12. MASON, http://cs.gmu.edu/~eclab/projects/mason (Luke et al., 2005)
  13. 13. Swarm, presently at http://savannah.nongnu.org/projects/swarm and MAML, http://www.maml.hu/maml/introduction/introduction.html, that uses easier code that translates to Swarm
  14. 15. Agent Modeling Platform (AMP), http://eclipse.org/amp
  15. 17. Cormas, a “natural resources and agent-based simulation” system, http://cormas.cirad.fr/en/outil/outil.htm
  16. 18. Agentbase, http://agentbase.org, a tool aimed at educational uses, with the capability of coding models in Coffeescript (a simplified version of Java, http://coffeescript.org) and running them on the browser

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.University of PiraeusPiraeusGreece

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