… Inspired by the success of Deep Reinforcement Learning (DRL) in solving … for content
caching decisions at an edge node, eg, a base station. Endusers keep requesting content from the …

… , we design a deep reinforcement learning (DRL)-based cooperative caching scheme to …
Particularly, we leverage a deep deterministic policy gradient (DDPG) learning algorithm to …

… cache content or resource allocation, this article comprehensively focuses on the jointly content
placement and content delivery policy of cache… the users’ mobility and content popularity. …

… In the content update phase, we propose to update the BS cache by taking into account
both the newly fetched contents and its cache in current time slot. The BS first evicts or retains …

… s content delivery networks such as Akamai [32], have tree network structures. Accounting for
the hierarchy of caches … Joint routing and innetwork content caching in a hierarchical cache …

… , we study content caching at the wireless network edge using a deep reinforcement learning
… In particular, we propose deep actorcritic reinforcement learning based policies for both …

… , we propose a deep reinforcement learning (DRL)-based vertically cooperative caching
strategy (… In the three-tier wireless network, the content requests are only sent or received at the …

… the issue of content-centric caching with QoE in an edge-enabled IoT. Aiming at caching
intelligence in this environment, a novel model is proposed to balance the QoE and the caching …

… In this paper, we propose dynamic cache content update scheduling algorithms that … deep
learning models are being cached in a heterogeneous network. A queue-aware cache content …

… Considering the large scale of online video contents and their time-varying popularity
distribution, we suggest that deep reinforcement learning is a promising method for effective cache …