Results 1 to 10 of about 5,156,964 (309)

Using reinforcement learning in genome assembly: in-depth analysis of a Q-learning assembler [PDF]

open access: yesFrontiers in Bioinformatics
Genome assembly remains an unsolved problem, and de novo strategies (i.e., those run without a reference) are relevant but computationally complex tasks in genomics.
Kleber Padovani   +7 more
doaj   +2 more sources

Reducing the Prevalence of Coronavirus (COVID-19) in Airlines Based on and the Reinforcement Artificial Intelligence [PDF]

open access: yesفناوری در مهندسی هوافضا, 2022
This paper proposes a method based on the artificial intelligence reinforcement Q-learning algorithm and paired comparison technique to solve the problem of health monitoring devices shortage in airlines.
Iman Shafieenejad   +3 more
doaj   +1 more source

Reinforcement learning using Deep $$Q$$ Q networks and $$Q$$ Q learning accurately localizes brain tumors on MRI with very small training sets

open access: yesBMC Medical Imaging, 2022
Background Supervised deep learning in radiology suffers from notorious inherent limitations: 1) It requires large, hand-annotated data sets; (2) It is non-generalizable; and (3) It lacks explainability and intuition.
J. N. Stember, H. Shalu
doaj   +1 more source

Reinforcement Learning-Based Routing Protocols in Vehicular and Flying Ad Hoc Networks – A Literature Survey

open access: yesPromet (Zagreb), 2022
Vehicular and flying ad hoc networks (VANETs and FANETs) are becoming increasingly important with the development of smart cities and intelligent transportation systems (ITSs).
Pavle Bugarčić   +2 more
doaj   +1 more source

QSPCA: A two-stage efficient power control approach in D2D communication for 5G networks

open access: yesIntelligent and Converged Networks, 2021
The existing literature on device-to-device (D2D) architecture suffers from a dearth of analysis under imperfect channel conditions. There is a need for rigorous analyses on the policy improvement and evaluation of network performance. Accordingly, a two-
Saurabh Chandra   +4 more
doaj   +1 more source

Cooperative Output Regulation By Q-learning For Discrete Multi-agent Systems In Finite-time

open access: yesJournal of Applied Science and Engineering, 2022
This article studies the output regulation of discrete-time multi-agent systems with an unknown model by a finite-time optimal control algorithm based on Q-learning that uses the method of the linear quadratic regulator (LQR).
Wenjun Wei, Jingyuan Tang
doaj   +1 more source

QIBMRMN: Design of a Q-Learning based Iterative sleep-scheduling & hybrid Bioinspired Multipath Routing model for Multimedia Networks [PDF]

open access: yesInternational Journal of Electronics and Telecommunications, 2023
Multimedia networks utilize low-power scalar nodes to modify wakeup cycles of high-performance multimedia nodes, which assists in optimizing the power-toperformance ratios.
Minaxi Doorwar, P Malathi
doaj   +1 more source

Methods and software for solar power plant cluster management

open access: yesAdaptivni Sistemi Avtomatičnogo Upravlinnâ, 2022
Object is solar power plant management software. Nowadays, solar panel production technologies are developing rapidly, investments in solar energy are growing, so users are interested in increasing energy production for faster return on investment.
А. Мокрий, І. Баклан
doaj   +1 more source

Adaptive Control of an Inverted Pendulum by a Reinforcement Learningbased LQR Method

open access: yesSakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2023
Inverted pendulums constitute one of the popular systems for benchmarking control algorithms. Several methods have been proposed for the control of this system, the majority of which rely on the availability of a mathematical model.
Uğur Yıldıran
doaj   +1 more source

Applying Deep Reinforcement Learning to Cable Driven Parallel Robots for Balancing Unstable Loads: A Ball Case Study

open access: yesFrontiers in Robotics and AI, 2021
The current pandemic has highlighted the need for rapid construction of structures to treat patients and ensure manufacturing of health care products such as vaccines.
Alex Grimshaw, John Oyekan
doaj   +1 more source

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