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Double Q-PID algorithm for mobile robot control
(Pergamon-Elsevier Science Ltd, 2019-12-15)
Many expert systems have been developed for self-adaptive PID controllers of mobile robots. However, the high computational requirements of the expert systems layers, developed for the tuning of the PID controllers, still ...
Energy enhancement using Multiobjective Ant colony optimization with Double Q learning algorithm for IoT based cognitive radio networks
Internet of Things (IoT) is the efficient wireless communication in the modern era, energy efficiency is the primary issue that focuses mainly on the Cognitive network. Most of the CR networks are focusing on battery ...
Recognition of Hand Gestures Based on EMG Signals with Deep and Double-Deep Q-Networks
(MDPI, 2023-04)
In recent years, hand gesture recognition (HGR) technologies that use electromyography (EMG) signals have been of considerable interest in developing human–machine interfaces. Most state-of-the-art HGR approaches are based ...
Double deep q-network no método de recuperação avançada injeção de água em um campo de petróleo
(Universidade Federal do Rio Grande do NorteBrasilUFRNPROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIA E ENGENHARIA DE PETRÓLEO, 2022-01-31)
It is necessary, for the best oil production, the constant development of new alternatives
for the exploitation of the fields. The need to optimize the factors involved in this
process requires great care in all the ...
Comparação de algoritmos de aprendizagem por reforço profundo na navegação do robô móvel e desvio de trajetória
(Universidade Federal de Santa MariaBrasilUFSMCentro de Tecnologia, 2022-09-23)
This work presents two Deep Reinforcement Learning (Deep-RL) approaches to enhance the problem of mapless navigation for a terrestrial mobile robot. The methodology focus on comparing a Deep-RL technique based on the Deep ...
Aceleração do Aprendizado por Reforço Aplicado ao Planejamento de Caminho para Robôs Transportadores de Cargas
(Universidade Federal de São Paulo, 2021-08-12)
Robôs autônomos vem ganhando espaço dentro da sociedade devido a sua grande gama de aplicações.
Uma utilização para robôs autônomos está no setor de transporte de produtos, entretanto
pensando no processo de locomoção ...
Sistema de navegación para robot móvil basado en aprendizaje por refuerzo
(Universidad de los AndesIngeniería ElectrónicaFacultad de IngenieríaDepartamento de Ingeniería Eléctrica y Electrónica, 2020)
En este proyecto de grado se aborda el problema de navegación para robots móviles utilizando aprendizaje por refuerzo profundo (Deep Reinforcement Learning o DRL). De forma especifica, se implementan algunas variantes de ...
Deep Q-learning
(Universidad de los AndesMatemáticasFacultad de CienciasDepartamento de Matemáticas, 2021)
Hemos estudiado e implementado una clase de algoritmos conocidos como deep Q-learning, inspirados en la mezcla entre el aprendizaje reforzado y el aprendizaje profundo. El objetivo principal de estos algoritmos es resolver ...
Energy management system for microgrids based on deep reinforcement learning
(Universidad de los AndesMaestría en Ingeniería EléctricaFacultad de IngenieríaDepartamento de Ingeniería Eléctrica y Electrónica, 2021)
The increasing use of distributed and renewable energy resources poses a challenge for traditional control methods. This happens due to the higher complexity and uncertainty introduced by these new technologies, specially ...
Defy the Game: Automated Market Making using Deep Reinforcement Learning
(Universidad Torcuato Di Tella, 2023)
Automated market makers have gained popularity in the financial market for their ability to provide
liquidity without needing a centralized intermediary (market maker). However, they suffer from the
problems of slippage ...