Using Active Queries to Infer Symmetric Node Functions of Graph Dynamical Systems
Using Active Queries to Infer Symmetric Node Functions of Graph Dynamical Systems
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发表时间：
2022
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通讯作者：
Abhijin Adiga;C. Kuhlman;M. Marathe;Sujith Ravi;D. Rosenkrantz;R. Stearns
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作者：
Abhijin Adiga;C. Kuhlman;M. Marathe;Sujith Ravi;D. Rosenkrantz;R. Stearns
开发技术来推断网络社会系统的行为在文献中引起了很大的关注。利用离散动力系统对网络社会系统进行建模，将系统的行为推断问题归结为动态系统局部函数的学习问题。我们在假设通过查询与系统进行主动交互的情况下研究该问题。我们考虑了两类局部函数(即对称函数和阈值函数)和两类局部函数
Developing techniques to infer the behavior of networked social systems has attracted a lot of attention in the literature. Using a discrete dynamical system to model a networked social system, the problem of inferring the behavior of the system can be formulated as the problem of learning the local functions of the dynamical system. We investigate the problem assuming an active form of interaction with the system through queries. We consider two classes of local functions (namely, symmetric and threshold functions) and two