@inproceedings{ca9d4387f87c4ca3a4e825df447cbe70,
title = "Stochastic Learning for the SET K-COVER Problem in Heterogeneous Wireless Sensor Networks",
abstract = "This paper addresses the SET K-COVER problem by proposing a memorial mixed-response algorithm (MMRA) from the perspective of learning in games, where each sensor node is viewed as a non-greedy game player with a limited memory and updates its action following a finite memory and a mixed response rule. We prove that our MMRA converges to a convention of Nash equilibria. Moreover, a tradeoff between solution efficiency and computation time could be achieved via the adjustment of the amount of randomness. Comparison results against typical distributed methods demonstrate the advantage of our methodology.",
keywords = "Convention, Nash equilibrium refinement, Potential game, SET K-COVER, Wireless sensor network (WSN)",
author = "Changhao Sun and Xiaochu Wang and Huaxin Qiu and Qingrui Zhou",
note = "Publisher Copyright: {\textcopyright} 2020 Technical Committee on Control Theory, Chinese Association of Automation.; 39th Chinese Control Conference, CCC 2020 ; Conference date: 27-07-2020 Through 29-07-2020",
year = "2020",
month = jul,
doi = "10.23919/CCC50068.2020.9189305",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "4521--4525",
editor = "Jun Fu and Jian Sun",
booktitle = "Proceedings of the 39th Chinese Control Conference, CCC 2020",
address = "美国",
}