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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 ...
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 Control of Signalized Intersections having Platoons
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Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Smart transportation cities are based on intelligent systems and data sharing while human drivers generally have limited capabilities and imperfect observations in traffics. The perception of Connected and Autonomous Vehicle ...
A Deep Reinforcement Learning Framework for Data Compression in Uplink NOMA-SWIPT Systems
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
<comment< Non-orthogonal multiple access (NOMA) shall play an important role in the current and foreseeable design of 5G and beyond networks. NOMA allows multiple users to share the same time-frequency ...
RL-PDNN: Reinforcement Learning for Privacy-Aware Distributed Neural Networks in IoT Systems
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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 ...
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 ...
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, ...
I-SEE: Intelligent, Secure, and Energy-Efficient Techniques for Medical Data Transmission Using Deep Reinforcement Learning
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
The rapid evolution of remote health monitoring applications is foreseen to be a crucial solution for facing an unpredictable health crisis and improving the quality of life. However, such applications come with many ...
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 ...