论文标题
分配和评估：在协作团队中实现最佳绩效
Assign and Appraise: Achieving Optimal Performance in Collaborative Teams
论文作者
论文摘要
解决复杂的团队问题需要了解每个团队成员的技能，以设计一个最大化团队绩效的任务任务。本文提出了一个新颖的定量模型，描述了一个分散的过程，团队中的个人通过该过程了解谁具有什么能力，同时将任务分配给每个团队成员。在模型中，评估网络代表团队成员对彼此的评估，每个团队成员选择了自己的工作量。评估和工作负载分配同时更改：每个成员根据先前任务的表现构建自己的本地成员评估，而工作量根据当前的评估估算重新分配。我们表明，由于存在与评估网络的周期相关的保守数量，因此可以将评估状态降低到较低的维度。在此基础上，我们提供了表征团队学习彼此技能的能力或无能为力的严格结果，从而融合了最大化团队绩效的分配。我们通过广泛的数值实验补充分析。
Tackling complex team problems requires understanding each team member's skills in order to devise a task assignment maximizing the team performance. This paper proposes a novel quantitative model describing the decentralized process by which individuals in a team learn who has what abilities, while concurrently assigning tasks to each of the team members. In the model, the appraisal network represents team member's evaluations of one another and each team member chooses their own workload. The appraisals and workload assignment change simultaneously: each member builds their own local appraisal of neighboring members based on the performance exhibited on previous tasks, while the workload is redistributed based on the current appraisal estimates. We show that the appraisal states can be reduced to a lower dimension due to the presence of conserved quantities associated to the cycles of the appraisal network. Building on this, we provide rigorous results characterizing the ability, or inability, of the team to learn each other's skill and thus converge to an allocation maximizing the team performance. We complement our analysis with extensive numerical experiments.
