Incentivizing Collaboration in Heterogeneous Teams via Common-Pool Resource Games

• 成果类型: Article
• 署名作者: Gupta, Piyush; Bopardikar, Shaunak D.; Srivastava, Vaibhav
• 署名单位: Michigan State University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3168498
• 发表日期: 2023
• 页码: 1902-1909
• 关键词: Task analysis; games; collaboration; Upper bound; Throughput; Queueing analysis; stability analysis; Best response potential; common-pool resource (CPR) game; pure Nash equilibrium (PNE); price of anarchy (PoA); tandem queues; utility design

摘要

We consider a team of heterogeneous agents, which is collectively responsible for servicing, and subsequently reviewing a stream of homogeneous tasks. Each agent has an associated mean service time and a mean review time for servicing and reviewing the tasks, respectively. Agents receive a reward based on their service and review admission rates. The team objective is to collaboratively maximize the number of serviced and reviewed tasks. We formulate a common-pool resource game, and design utility functions to incentivize collaboration among heterogeneous agents in a decentralized manner. We show the existence of a unique pure Nash equilibrium (PNE), and establish convergence of the best response dynamics to this unique PNE. Finally, we establish an analytic upper bound on three inefficiency measures of the PNE, namely the price of anarchy, the ratio of the total review admission rate, and the ratio of latency.