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Assign and Appraise Achieving Optimal Performance in Collaborative Teams

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Document pages: 13 pages

Abstract: Tackling complex team problems requires understanding each team member sskills in order to devise a task assignment maximizing the team performance.This paper proposes a novel quantitative model describing the decentralizedprocess by which individuals in a team learn who has what abilities, whileconcurrently assigning tasks to each of the team members. In the model, theappraisal network represents team member s evaluations of one another and eachteam member chooses their own workload. The appraisals and workload assignmentchange simultaneously: each member builds their own local appraisal ofneighboring members based on the performance exhibited on previous tasks, whilethe workload is redistributed based on the current appraisal estimates. We showthat the appraisal states can be reduced to a lower dimension due to thepresence of conserved quantities associated to the cycles of the appraisalnetwork. Building on this, we provide rigorous results characterizing theability, or inability, of the team to learn each other s skill and thusconverge to an allocation maximizing the team performance. We complement ouranalysis with extensive numerical experiments.

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