Complexity theory and collaboration: An agent-based simulator for a space mission design team



In this paper, we investigate how complexity theory can benefit collaboration by applying an agent-based computer simulation approach to a new form of synchronous real-time collaborative engineering design. Fieldwork was conducted with a space mission design team during their actual design sessions, to collect data on their group conversations, team interdependencies, and error monitoring and recovery practices. Based on the fieldwork analysis, an agent-based simulator was constructed. The simulation shows how error recovery and monitoring is affected by the number of small group, or sidebar, conversations, and consequent noise in the room environment. This simulation shows that it is possible to create a virtual environment with cooperating agents interacting in a dynamic environment. This simulation approach is useful for identifying the best scenarios and eliminating potential catastrophic combinations of parameters and values, where error recovery and workload in collaborative engineering design could be significantly impacted. This approach is also useful for defining strategies for integrating solutions into organizations.


Extreme collaboration Collaborative design Complexity theory Agent-based modeling and simulation Map of interdependencies Errors Sidebar conversations 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Axelrod, R, Cohen MD (2000) Harnessing complexity: Organizational implications of a scientific frontier. Free PressGoogle Scholar
  2. Axelrod R (1997) The complexity of cooperation: Agent based models of competition and collaboration. Princeton, Princeton University Press, New JerseyGoogle Scholar
  3. Ballot G, Weisbuch G (2000) Editors of applications of simulation to social sciences. In: Proceedings of the Second International Conference on Computer Simulations and the Social Sciences, Paris, September 18–20, Hermes Science Publications, ParisGoogle Scholar
  4. Bar-Yam Y (2000) Editor-in-chief of unifying themes in complex systems. In: Proceedings from the International Conference on Complex Systems. Advanced Book Program, Perseus Books, Cambridge, MassachusettsGoogle Scholar
  5. Cannon-Bowers JA, Salas E (2001) Reflections on shared cognition. J Organ Behav 22:195–202CrossRefGoogle Scholar
  6. Cannon-Bowers JA, Salas E, Converse S (1993) Shared mental models in expert team decision-making. In: Castellan J (ed) Individual and Group Decision-Making: Current issues: 221. LEA Publishers, pp 221–246Google Scholar
  7. Carley K (2001) Intra-organizationl complexity and computation. In: Baum JC (ed) Companion to organizations, Blackwell, Oxford UKGoogle Scholar
  8. Carley K (1997) Extracting team mental models through textual analysis. J Organ Behav 18:533–558CrossRefGoogle Scholar
  9. Carley K (1996) Validating Computational Models (working paper). Available at http://www.heinz.cmu. edu/wpapers/author.jsp?id=carley
  10. Cherry EC (1953) Some experiments upon the recognition of speech, with one and with two ears. J Acoust Soc Amer 25:975–279CrossRefGoogle Scholar
  11. Dent EB (1999) Complexity science: A worldview shift. Emergence 1(4)Google Scholar
  12. Dugdale J, Pavard B, Soubie JL (2000) A pragmatic development of a computer simulation of an emergency call centre. In: Dieng R, Giboin A, Karsenty L, De Michelis G (eds). Designing Cooperative Systems: The Use of Theories and Models. IOS PressGoogle Scholar
  13. Goldstein J (1999) Emergence as a construct: History and Issues. Emergence 1(1)Google Scholar
  14. Hollingshead AB (2000) Perceptions of expertise and transactive memory in work relationships. Group Processes & Intergroup Relations 3(3):257–267CrossRefGoogle Scholar
  15. Keyser D (2000) Emergent properties and behavior of the atmosphere. In: Bar-Yam Yaneer (ed) Proceedings from the International Conference on Complex Systems. Advanced Book Program, Perseus Books, Cambridge, MA, pp 33–41Google Scholar
  16. Klimoski R, Mohammed S (1994) Team mental model: Construct or metaphor? J Manag 20(2):403–437CrossRefGoogle Scholar
  17. Kreft JU, Booth G, Wimpenny JWT (1998) BacSim, a simulator for individual-based modeling of bacterial colony growth. Biology 144Google Scholar
  18. Levesque LL, Wilson JM, Wholey DR (2001) Cognitive divergence and shared mental models in software development project teams. J Organ Behav 22:135–144CrossRefGoogle Scholar
  19. Liang DW, Moreland R, Argote L (1995) Group versus individual training and group performance: The mediating role of transactive memory. Pers Soc Psychol Bull 21(4):384–393CrossRefGoogle Scholar
  20. Lissack MR (1999) Complexity: The science, its vocabulary and its relation to Organizations. Emergence 1(1)Google Scholar
  21. Mark G (2002) Extreme collaboration. Commun ACM 45(6):89–93CrossRefGoogle Scholar
  22. McKelvey B (1999) Complexity theory in organization science: Seizing the promise or becoming a fad? Emergence 1(1)Google Scholar
  23. Olson JS, Covi L, Rocco E, Miller, JW, Allie PA (1998) Room of your own: What would it take to help remote groups work as well as collocated groups?. In: Proceedings of CHI' 98Google Scholar
  24. Pavard B, Dugdale J (2000) The contribution of complexity theory to the study of socio-technical cooperative systems. InterJournal: New England Complex Institute Electronic journalGoogle Scholar
  25. Pavard B, Dugdale J (2001) An introduction to complexity in social science. http://www.irit. fr/COSI/ training/complexity-tutorial/complexity-tutorial.tml
  26. Simon HA (1969) The sciences of the artificial. MIT Press, Cambridge, MAGoogle Scholar
  27. Strader TJ, Lin FR, Shaw MJ (1998) Simulation of order fulfillment in divergent assembly supply chains. J Art Soc Social Simul 1(2)Google Scholar
  28. Teasley S, Covi L, Krishnan MS, Olson JS (2000) How does radical collocation help a team succeed?. In: Proceedings of CSCW2000, ACM Press, New YorkGoogle Scholar
  29. Terano T (2000) Analyzing social interaction in electronic communities using an artificial world approach. Technol Forecast Soc Change 64Google Scholar
  30. Weick KE (1979) The social psychology of organizing. McGraw-Hill, New YorkGoogle Scholar

Copyright information

© Springer Science + Business Media, LLC 2006

Authors and Affiliations

  1. 1.RIADI-GDL LaboratoryUniversity of TunisTunisTunisia
  2. 2.Department of InformaticsUniversity of CaliforniaIrvineUSA

Personalised recommendations