Optimal Fidelity Selection for Human-in-the-loop Queues using Semi-Markov Decision Processes

被引:8
作者
Gupta, Piyush [1 ]
Srivastava, Vaibhav [1 ]
机构
[1] Michigan State Univ, Dept Elect & Comp Engn, E Lansing, MI 48824 USA
来源
2019 AMERICAN CONTROL CONFERENCE (ACC) | 2019年
关键词
D O I
10.23919/acc.2019.8814842
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We study optimal fidelity selection for a human operator servicing a queue of homogeneous tasks. The service time distribution of the human operator depends on her cognitive dynamics and the level of fidelity selected for servicing the task. Cognitive dynamics of the operator evolve as a Markov chain in which the cognitive state increases (decreases) with high probability whenever she is busy (resting). The tasks arrive according to a Poisson process and each task waiting in the queue loses its value at a fixed rate. We address the trade-off between high quality service of a task and consequent loss in value of future tasks using a Semi-Markov Decision Process (SMDP) framework. We numerically determine an optimal policy and establish its structural properties.
引用
收藏
页码:5266 / 5271
页数:6
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