Listar por tema "reinforcement learning"
Mostrando ítems 1-8 de 8
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Deep Reinforcement Learning aplicado a un módulo experimental del acelerador de IFMIF-DONES
(19/09/2023)Aunque la fusión nuclear tiene el potencial de ser una fuente de energía renovable y limpia, su extracción se enfrenta a desafíos importantes, como el estudio de los efectos de la irradiación de neutrones en los materiales ... -
Enhanced resource allocation in mobile edge computing using reinforcement learning based MOACO algorithm for IIOT
(Computer Communications, 01/02/2020)The Mobile networks deploy and offers a multiaspective approach for various resource allocation paradigms and the service based options in the computing segments with its implication in the Industrial Internet of Things ... -
Estudio de rendimiento de agentes inteligentes que juegan al juego del iwoki
(13/02/2020)El iwoki maths es un juego de mesa abstracto de colocación de losetas. Combina el cálculo de operaciones matemáticas simples con la percepción espacial de objetos bidimensionales. Se desarrollará una serie de agentes ... -
Instance-based defense against adversarial attacks in Deep Reinforcement Learning
(Elsevier Ltd, 2022)Deep Reinforcement Learning systems are now a hot topic in Machine Learning for their effectiveness in many complex tasks, but their application in safety-critical domains (e.g., robot control or self-autonomous driving) ... -
Integración de aprendizaje por imitación y refuerzo con realidad virtual
(15/07/2021)En este proyecto se muestra una vía para entrenar agentes inteligentes capaces de realizar tareas de manipulación en entornos complejos. Para ello se ha creado un entorno utilizando el motor gráfico Unity para, posteriormente, ... -
Performance Study of Minimax and Reinforcement Learning Agents Playing the Turn-based Game Iwoki
(Bellwether Publishing, Ltd., 2021)Iwoki math is an abstract board game that consists on placing tiles and that combines the calculation of simple mathematical operations with the spatial perception of two-dimensional objects. Due to its inherent features, ... -
Quantum-Annealed Action Selection Policy for Reinforcement Learning
(01/07/2023)De entre todos los tipos de machine learning, el aprendizaje por refuerzo es posiblemente el menos estudiado en t´erminos de computaci´on cu´antica, si bien tiene potencial para beneficiarse en gran medida del no-determinismo ... -
Short-term forecasting electricity load by long short-term memory and reinforcement learning for optimization of hyper-parameters
(Evolutionary Intelligence, 2023)Electricity load forecasting is an essential operation of the power system. Deep learning is used to improve accurate electricity load forecasting. In this study, combining Long short-term memory and reinforcement learning ...
