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Effect of Humans on Belief Propagation in Large Heterogeneous Teams

In: Dynamics of Information Systems

Author

Listed:
  • Praveen Paruchuri

    (Carnegie Mellon University)

  • Robin Glinton

    (Carnegie Mellon University)

  • Katia Sycara

    (Carnegie Mellon University)

  • Paul Scerri

    (Carnegie Mellon University)

Abstract

Summary Members of large, heterogeneous teams often need to interact with different kinds of teammates to accomplish their tasks, teammates with dramatically different capabilities to their own. While the role of humans in teams has progressively decreased with the deployment of increasingly intelligent systems, they still have a major role to play. In this chapter, we focus on the role of humans in large, heterogeneous teams that are faced with situations, where there is a large volume of incoming, conflicting data about some important fact. We use an abstract model of both humans and agents to investigate the dynamics and emergent behaviors of large teams trying to decide whether some fact is true. In particular, we focus on the role of humans in handling noisy information and their role in convergence of beliefs in large heterogeneous teams. Our simulation results show that systems involving humans exhibit an enabler-impeder effect, where if humans are present in low percentages, they aid in propagating information; however when the percentage of humans increase beyond a certain threshold, they seem to impede the information propagation.

Suggested Citation

  • Praveen Paruchuri & Robin Glinton & Katia Sycara & Paul Scerri, 2010. "Effect of Humans on 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 183-196, Springer.
    • Handle: RePEc:spr:spochp:978-1-4419-5689-7_9
    DOI: 10.1007/978-1-4419-5689-7_9
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