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Self-Organized Criticality of Belief Propagation in Large Heterogeneous Teams

In: Dynamics of Information Systems

Author

Listed:
  • Robin Glinton

    (Carnegie Mellon University)

  • Praveen Paruchuri

    (Carnegie Mellon University)

  • Paul Scerri

    (Carnegie Mellon University)

  • Katia Sycara

    (Carnegie Mellon University)

Abstract

Summary Large, heterogeneous teams will often be faced with situations where there is a large volume of incoming, conflicting data about some important fact. Not every team member will have access to the same data and team members will be influenced most by the teammates with whom they communicate directly. In this paper, we use an abstract model to investigate the dynamics and emergent behaviors of a large team trying to decide whether some fact is true. Simulation results show that the belief dynamics of a large team have the properties of a Self-Organizing Critical system. A key property of such systems is that they regularly enter critical states, where one additional input can cause dramatic, system wide changes. In the belief sharing case, this criticality corresponds to a situation where one additional sensor input causes many agents to change their beliefs. This can include the entire team coming to a “wrong” conclusion despite the majority of the evidence suggesting the right conclusion. Self-organizing criticality is not dependent on carefully tuned parameters, hence the observed phenomena are likely to occur in the real world.

Suggested Citation

  • Robin Glinton & Praveen Paruchuri & Paul Scerri & Katia Sycara, 2010. "Self-Organized Criticality of Belief Propagation in Large Heterogeneous Teams," Springer Optimization and Its Applications, in: Michael J. Hirsch & Panos M. Pardalos & Robert Murphey (ed.), Dynamics of Information Systems, chapter 0, pages 165-182, Springer.
  • Handle: RePEc:spr:spochp:978-1-4419-5689-7_8
    DOI: 10.1007/978-1-4419-5689-7_8
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