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Closed-loop control of anesthesia and mean arterial pressure using reinforcement learning
(
IEEE
, 2014 , Conference Paper)
General anesthesia is required for patients undergoing surgery as well as for some patients in the intensive care units with acute respiratory distress syndrome. How-ever, most anesthetics affect cardiac and respiratory ...
State-dependent adaptive dynamic programing for a class of continuous-time nonlinear systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Conference Paper)
The state-dependent Riccati equation (SDRE) technique can be used to solve optimal control problems for a wide class of nonlinear dynamical systems. In this method, instead of solving a complicated Hamilton-Jacobi-Bellman ...
Real-Time Scheduling for Electric Vehicles Charging/Discharging Using Reinforcement Learning
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
With the increase in Electric Vehicles (EVs) penetration, their charging needs form an additional burden on the grid. Thus, charging coordination is necessary for safe and efficient EV use. The scheduling of EVs is especially ...
Optimal cooperative cognitive relaying and spectrum access for an energy harvesting cognitive radio: Reinforcement learning approach
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
In this paper, we consider a cognitive setting under the context of cooperative communications, where the cognitive radio (CR) user is assumed to be a self-organized relay for the network. The CR user and the primary user ...
Distributed interference management using Q-Learning in cognitive femtocell networks: New USRP-based implementation
(
Institute of Electrical and Electronics Engineers Inc.
, 2015 , Conference Paper)
Femtocell networks have become a promising solution in supporting high data rates for 5G systems, where cell densification is performed using the small femtocells. However, femtocell networks have many challenges. One of ...
Rational Contracts: Data-driven Service Provisioning in Blockchain-powered Systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
Smart Contracts (SCs), which are software programs that run on blockchain platforms, provide appealing security guarantees characterized by decentralized, autonomous, and verifiable execution. On the other hand, Service ...
Deep Reinforcement Learning Algorithm for Smart Data Compression under NOMA-Uplink Protocol
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
One of the highly promising radio access strategies for enhancing performance in the next generation cellular communications is non-orthogonal multiple access (NOMA). NOMA offers a number of advantages including better ...
Energy-efficient networks selection based deep reinforcement learning for heterogeneous health systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
Smart health systems improve the existing health services by integrating information and technology into health and medical practices. However, smart healthcare systems are facing major challenges including limited network ...
A cooperative Q-learning approach for distributed resource allocation in multi-user femtocell networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Conference Paper)
This paper studies distributed interference management for femtocells that share the same frequency band with macrocells. We propose a multi-agent learning technique based on distributed Q-learning, called subcarrier-based ...
Smart and Secure Blockchain-based Healthcare System Using Deep Q-Learning
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
Healthcare is one of the top priorities in modern society to provide better health facilities. Therefore, investments in health care systems increased rapidly, aligned with the population growth rate. Besides, the data ...