… and the caching procedures. In this article, we propose security solutions that apply
reinforcement learning (RL) techniques to provide secure offloading to the edge nodes against …

… decide the video files to be cached at the MEC servers. In this paper, we propose a multi-agent
reinforcement learning (MARL)-based cooperative content caching policy for the MEC …

… the edge caching problem in a … reinforcement-learning-based cooperative edge caching
algorithm (FADE), which enables IoT devices [or user equipment (UE)]1 to cooperatively learn …

… In this context, the fetch-andreplace strategy in the cache miss case may not … caching network
to improve cache hit rate in the BS. To our best knowledge, few existing work on the cache …

… edge caching framework that explores both adaptive intelligence and collaborative intelligence
so as to better boost the edge caching … Inspired by the recent advances of learning in …

… related to DRL in mobile edge caching. First, we introduce the preliminaries of edge caching,
and … Second, we review the state-of-the-art learning-based mobile edge caching schemes. …

… content caching. For centralized edge caching, we aim at maximizing the cache hit rate. In
decentralized edge caching, we consider both the cache hit rate and transmission delay as …

… , edge caching (EC) optimization is crucial to the effective utilization of the caching resources
in … (P2D3PG) algorithm is proposed to maximize the cache hit rates of devices in the MEC …

… Abstract—This paper studies the joint communication, caching and computing design problem
… We develop a deep reinforcement learning with the multi-timescale framework to tackle …

… to learn a series of intelligence behaviors. With the aid of intelligence of natural-inspired
approaches, we design a deep reinforcement learning (DRL)-based cooperative caching …