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Coalition Formation: From Software Agents to Robots

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Abstract

A problem that has recently attracted the attention of the research community is the autonomous formation of robot teams to perform complex multi-robot tasks. The corresponding problem for software agents is also known in the multi-agent community as the coalition formation problem. Numerous algorithms for software agent coalition formation have been provided that allow for efficient cooperation in both competitive and cooperative environments. However, despite the plethora of relevant literature on the software agent coalition formation problem, and the existence of similar problems in theoretical computer science, the multi-robot coalition formation problem has not been sufficiently grounded for different tasks and task environments. In this paper, comparisons are drawn to highlight the differences between software agents and robotics, and parallel problems from theoretical computer science are identified. This paper further explores robot coalition formation in different practical robotic environments. A heuristic-based coalition formation algorithm from our previous work was extended to operate in precedence ordered cooperative environments. In order to explore coalition formation in competitive environments, the paper also studies the RACHNA system, a market based coalition formation system. Finally, the paper investigates the notion of task preemption for complex multi-robot tasks in random allocation environments.

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  1. Electrical Engineering and Computer Science Department, Vanderbilt University, Nashville, TN, 37212, USA

    Lovekesh Vig & Julie A. Adams

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  1. Lovekesh Vig
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  2. Julie A. Adams
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Correspondence to Lovekesh Vig.

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Manuscript submitted on the 1st of September 2006, Lovekesh Vig is a graduate student in the EECS Department at Vanderbilt University, Nashville TN 37212. Julie A. Adams is a Assistant Professor in the EECS Department at Vanderbilt University, Nashville TN 37212.

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Vig, L., Adams, J.A. Coalition Formation: From Software Agents to Robots. J Intell Robot Syst 50, 85–118 (2007). https://doi.org/10.1007/s10846-007-9150-0

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