… This paper constructs a three-layer offloading framework in intelligent Internet of Vehicles
(IoV) to … After that, a deep reinforcement learning-based scheme is put forward to solve the …

… For dynamic network clustering, the actor-critic based DRL is employed as the deep
reinforcement learning model in this paper. The reinforcement learning (RL) consists of set of state-…

… In recent times, there have been attempts to integrate deep reinforcement learning (DRL) …
Wang, “Diversified technologies in Internet of vehicles under intelligent edge computing,” …

… In this paper, we develop an intent-based traffic control system by investigating Deep
Reinforcement Learning (DRL) for 5G-envisioned IoCVs, which can dynamically orchestrate edge …

… communication networks, and proposed a deep reinforcement learning approach to make
the … By a deep reinforcement learning approach [30], we solve the vehicle’s cost minimization …

… for the internet of vehicles (IoV). To meet the low latency of vehicle tasks offloading, an
offloading scheme combining mobile edge computing (MEC) and deep reinforcement learning (…

… Deep reinforcement learning (DRL) has recently caused … the edge cache of the Internet of
vehicles with DRL algorithm for … analyzes edge caching for Internet of Vehicles, and proposes …

… Especially, we focus on the Internet of Vehicles scenario, which needs the support of mobile
network provided by MNO. We first formulate an optimization problem to minimize MNO’s …

… We propose a deep reinforcement learning approach to provide an intelligent policy for
RSUs collaborative caching and collaborative transport between V2R and V2V. The …

… In the typical scenario of the Internet of Vehicles (IoV), the edge … To tackle it, a deep
reinforcement learning-based multi-… problem is formulated and the deep reinforcement learning, …