Most of the existing anti-jamming decision-making methods overly rely on the subjective
experience of radar operators. However, due to the rapid development of cognitive radar …

In multiagent domains, coping with non-stationary agents that change behaviors from time to
time is a challenging problem, where an agent is usually required to be able to quickly …

Future AI applications require performance, reliability and privacy that the existing, cloud-
dependant system architectures cannot provide. In this article, we study orchestration in the …

多Agent深度强化学习综述 E-mail Alert RSS 2.765 2022影响因子 (CJCR) 中文核心 EI 中国科技
核心 Scopus CSCD 英国科学文摘 首页 期刊介绍 1.基本信息 2.收录与获奖 3.近年指标 期刊在线 …

By leveraging the concept of mobile edge computing (MEC), massive amount of data
generated by a large number of Internet of Things (IoT) devices could be offloaded to MEC …

Designing intelligent agents that interact proficiently with people necessitates the prediction
of human decision-making. We present and discuss three prediction paradigms for …

Distributed energy resources (DERs), such as solar panels, are growing rapidly and
reshaping power systems. To promote DERs, utility companies usually adopt feed-in-tariff …

We consider a homogeneous cellular network where a multi-antenna base station (BS) in
each cell transmits messages to its intended user over a common frequency band. To …

Learning in multi-agent environments is difficult due to the non-stationarity introduced by an
opponent's or partner's changing behaviors. Instead of reactively adapting to the other …

Modelling the behaviours of other agents is essential for understanding how agents interact
and making effective decisions. Existing methods for agent modelling commonly assume …