Listar LCC - Artículos por título
Mostrando ítems 99-112 de 112
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A temporal difference method for multi-objective reinforcement learning
This work describes MPQ-learning, an temporal-difference method that approximates the set of all non-dominated policies in multi-objective Markov decision problems, where rewards are vectors and each component stands for ... -
The component model for elementary landscapes and partial neighborhoods
Whitley, L. Darrell; Sutton, Andrew M.; Ochoa, Gabriela; Chicano-García, José-Francisco
(2014-09-29)
Local search algorithms exploit moves on an adjacency graph of the search space. An “elementary landscape” exists if the objective function f is an eigenfunction of the Laplacian of the graph induced by the neighborhood ... -
The orchestration of Machine Learning frameworks with datastreams and GPU acceleration in Kafka-ML: A deep-learning performance comparative
Machine Learning (ML) applications need large volumes of data to train their modelsso that they can make high-quality predictions. Given digital revolution enablers suchas the Internet of Things (IoT) and the Industry 4.0, ... -
The software project scheduling problem: A scalability analysis of multi-objective metaheuristics
Luna, Francisco; González-Álvarez, David L.; Chicano-García, José-Francisco; Vega-Rodríguez, Miguel A. (2014-10-02)
Computer aided techniques for scheduling software projects are a crucial step in the software development process within the highly competitive software industry. The Software Project Scheduling (SPS) problem relates to ... -
The use of observations of soft X-rays and protons in the UMASEP scheme for making real-time predictions of the SEP events that took place in july and september 2017
Núñez-Paz, Marlon (IOAP-MDPI, 2022-01-07)
The prediction of solar energetic particle (SEP) events may help to improve the mitigation of adverse effects on humans and technology in space. UMASEP (University of Málaga Solar particle Event Predictor) is an empirical ... -
TITAN: A knowledge-based platform for Big Data workflow management
Benítez-Hidalgo, Antonio; Barba-González, Cristóbal; Gutiérrez-Moncayo, Pedro; Paneque, Manuel; Nebro-Urbaneja, Antonio Jesús; Roldán-García, María del Mar; Aldana-Montes, José Francisco; Navas-Delgado, Ismael[et al.] (ELSEVIER, 2021-11-28)
Modern applications of Big Data are transcending from being scalable solutions of data processing and analysis, to now provide advanced functionalities with the ability to exploit and understand the underpinning knowledge. ... -
Transforming numerical feature models into propositional formulas and the universal variability language
Muñoz-Guerra, Daniel Jesús; Pinto-Alarcón, Mónica; Fuentes-Fernández, Lidia; Batory, Don (Elsevier, 2023)
Real-world Software Product Lines (SPLs) need Numerical Feature Models (NFMs) whose features have not only boolean values that satisfy boolean constraints but also have numeric attributes that satisfy arithmetic constraints. ... -
Using Bayesian networks to improve knowledge assessment
Millán-Valldeperas, Eva; Descalço, Luis; Castillo, Gladys; Oliveira, Paula; Diogo, Sandra (Elsevier, 2013-01)
In this paper, we describe the integration and evaluation of an existing generic Bayesian student model (GBSM) into an existing computerized testing system within the Mathematics Education Project (PmatE - Projecto ... -
Using machine learning techniques for architectural design tracking: an experimental study of the design of a shelter
Millán-Valldeperas, Eva; Belmonte-Martínez, María Victoria; Boned-Purkiss, Francisco Javier; Gavilanes-Velaz-de-Medrano, Juan; Pérez-de-la-Cruz-Molina, José Luis; Díaz-López, Carmen[et al.] (Elsevier, 2022)
In this paper, we present a study aimed at tracking and analysing the design process. More concretely, we intend to explore whether some elements of the conceptual design stage in architecture might have an influence on ... -
Using machine learning techniques for architectural design tracking: An experimental study of the design of a shelter
Millán-Valldeperas, Eva; Belmonte-Martínez, María Victoria; Boned-Purkiss, Francisco Javier; Gavilanes-Velaz-de-Medrano, Juan; Pérez-de-la-Cruz-Molina, José Luis; Díaz-López, Carmen[et al.] (Elsevier, 2022-07-22)
In this paper, we present a study aimed at tracking and analysing the design process. More concretely, we intend to explore whether some elements of the conceptual design stage in architecture might have an influence on ... -
Using SPL to Develop AAL Systems Based on Self-adaptive Agents
Amor-Pinilla, María Mercedes; Ayala-Viñas, Inmaculada; Fuentes-Fernández, Lidia (Springer, 2016-06)
Abstract One of the most important challenges of this decade is the Internet of Things (IoT) that pursues the integration of real-world objects in Internet. One of the key areas of the IoT is the Ambient Assisted Living ... -
Vida artificial: en la encrucijada
(Universidad de Málaga, 2014-06-13)En las últimas décadas, la línea divisoria entre la Biología y las Ciencias de la Computación se ha ido difuminando paulatinamente. Por un lado, una gran cantidad de métodos computacionales (colectivamente conocidos como ... -
Virtual player design using self-learning via competitive coevolutionary algorithms
Nogueira-Collazo, Mariela; Cotta-Porras, Carlos; Fernández-Leiva, Antonio José (Springer, 2014-06)
The Google Artificial Intelligence (AI) Challenge is an international contest the objective of which is to program the AI in a two-player real time strategy (RTS) game. This AI is an autonomous computer program that governs ... -
Walk-IT: An Open-Source Modular Low-Cost Smart Rollator
Fernández-Carmona, Manuel; Ballesteros-Gómez, Joaquín; Díaz-Boladeras, María; Parra-Llanas, Xavier; Urdiales-García, Amalia Cristina; Gómez-de-Gabriel, Jesús Manuel[et al.] (IOAP-MPDI, 2022-03-08)
Rollators are widely used in clinical rehabilitation for gait assessment, but gait analysis usually requires a great deal of expertise and focus from medical staff. Smart rollators can capture gait parameters autonomously ...