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Reinforcement learning-based decision support system for COVID-19
(
Elsevier
, 2021 , Article)
Globally, informed decision on the most effective set of restrictions for the containment of COVID-19 has been the subject of intense debates. There is a significant need for a structured dynamic framework to model and ...
Reinforcement learning-based school energy management system
(
MDPI AG
, 2020 , Article)
Energy efficiency is a key to reduced carbon footprint, savings on energy bills, and sustainability for future generations. For instance, in hot climate countries such as Qatar, buildings are high energy consumers due to ...
Reinforcement learning approaches for efficient and secure blockchain-powered smart health systems
(
Elsevier B.V.
, 2021 , Article)
Emerging technological innovation toward e-Health transition is a worldwide priority for ensuring people's quality of life. Hence, secure exchange and analysis of medical data amongst diverse organizations would increase ...
To chain or not to chain: A reinforcement learning approach for blockchain-enabled IoT monitoring applications
(
Elsevier B.V.
, 2020 , Article)
Traceability and autonomous business logic execution are highly desirable features in IoT monitoring applications. Traceability enables verifying signals history for security or analytical purposes. On the other hand, the ...
RL-PDNN: Reinforcement Learning for Privacy-Aware Distributed Neural Networks in IoT Systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Due to their high computational and memory demand, deep learning applications are mainly restricted to high-performance units, e.g., cloud and edge servers. Particularly, in Internet of Things (IoT) systems, the data ...
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, ...
Reinforcement learning-based control of tumor growth under anti-angiogenic therapy.
(
Elsevier
, 2019 , Article)
In recent decades, cancer has become one of the most fatal and destructive diseases which is threatening humans life. Accordingly, different types of cancer treatment are studied with the main aim to have the best treatment ...
On Designing Smart Agents for Service Provisioning in Blockchain-powered Systems
(
IEEE Computer Society
, 2021 , 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 ...
Optimal adaptive control of drug dosing using integral reinforcement learning
(
Elsevier Inc.
, 2019 , Article)
In this paper, a reinforcement learning (RL)-based optimal adaptive control approach is proposed for the continuous infusion of a sedative drug to maintain a required level of sedation. To illustrate the proposed method, ...
Reinforcement learning-based control of drug dosing for cancer chemotherapy treatment
(
Elsevier Inc.
, 2017 , Article)
The increasing threat of cancer to human life and the improvement in survival rate of this disease due to effective treatment has promoted research in various related fields. This research has shaped clinical trials and ...