Browsing by Subject "Deep reinforcement learning"
Now showing items 1-6 of 6
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Deep Reinforcement Learning for Network Selection over Heterogeneous Health Systems
( IEEE Computer Society , 2022 , Article)Smart health systems improve our quality oflife by integrating diverse information and technologies into health and medical practices. Such technologies can significantly improve the existing health services. However, ... -
Deep Reinforcement Learning for Real-Time Trajectory Planning in UAV Networks
( Institute of Electrical and Electronics Engineers Inc. , 2020 , Conference Proceedings)In Unmanned Aerial Vehicle (UAV)-enabled wireless powered sensor networks, a UAV can be employed to charge the ground sensors remotely via Wireless Power Transfer (WPT) and collect the sensory data. This paper focuses on ... -
DRL-HEMS: Deep Reinforcement Learning Agent for Demand Response in Home Energy Management Systems Considering Customers and Operators Perspectives
( Institute of Electrical and Electronics Engineers Inc. , 2022 , Article)With the smart grid and smart homes development, different data are made available, providing a source for training algorithms, such as deep reinforcement learning (DRL), in smart grid applications. These algorithms allowed ... -
A graph convolutional network-based deep reinforcement learning approach for resource allocation in a cognitive radio network
( MDPI , 2020 , Article)Cognitive radio (CR) is a critical technique to solve the conflict between the explosive growth of traffic and severe spectrum scarcity. Reasonable radio resource allocation with CR can effectively achieve spectrum sharing ... -
Microservice instances selection and load balancing in fog computing using deep reinforcement learning approach
( Elsevier , 2024 , Article)Fog-native computing is an emerging paradigm that makes it possible to build flexible and scalable Internet of Things (IoT) applications using microservice architecture at the network edge. With this paradigm, IoT applications ... -
On Designing Smart Agents for Service Provisioning in Blockchain-Powered Systems
( IEEE Computer Society , 2022 , Article)Service provisioning systems assign users to service providers according to allocation criteria that strike an optimal trade-off between users' Quality of Experience (QoE) and the operation cost endured by providers. These ...