Swarm Intelligence

, Volume 10, Issue 2, pp 147–160 | Cite as

Modeling multi-robot task allocation with limited information as global game

Article

Abstract

Continuous response threshold functions to coordinate collaborative tasks in multi-agent systems are commonly employed models in a number of fields including ethology, economics, and swarm robotics. Although empirical evidence exists for the response threshold model in predicting and matching swarm behavior for social insects, there has been no formal argument as to why natural swarms use this approach and why it should be used for engineering artificial ones. In this paper, we show, by formulating task allocation as a global game, that continuous response threshold functions used for communication-free task assignment result in system level Bayesian Nash equilibria. Building up on these results, we show that individual agents not only do not need to communicate with each other, but also do not need to model each other’s behavior, which makes this coordination mechanism accessible to very simple agents, suggesting a reason for their prevalence in nature and motivating their use in an engineering context.

Keywords

Threshold-based task allocation Swarm robotics Social insects Game theory Global games 

Notes

Acknowledgments

A. Kanakia and N. Correll have been supported by NSF CAREER Grant #1150223. We are grateful for this support.

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.College of Engineering and Applied SciencesUniversity of Colorado BoulderBoulderUSA
  2. 2.Department of Computer ScienceUniversity of Colorado BoulderBoulderUSA
  3. 3.Department of Electrical, Computer and Energy EngineeringUniversity of Colorado BoulderBoulderUSA

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