J. J. Merelo
University of Granada
12 Papers
65 Citations
J. J. Merelo is an academic researcher from University of Granada. The author has contributed to research in topics: Evolutionary computation & SOAP. The author has an hindex of 7, co-authored 12 publications.
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Papers
Metaheuristics “In the Large”
Jerry Swan,Steven Adriaensen,Alexander E. I. Brownlee,Kevin Hammond,Colin G. Johnson,Ahmed Kheiri,Faustyna Krawiec,J. J. Merelo,Leandro L. Minku,Ender Özcan,Gisele L. Pappa,Pablo García-Sánchez,Kenneth Sörensen,Stefan Voß,Markus Wagner,David White +15 more
TL;DR: The metaheuristics "In the Large" project as discussed by the authors aims to support the development, analysis, and comparison of new approaches in optimization research by providing extensible algorithm templates that support reuse without modification, white box problem descriptions that provide generic support for the injection of domain specific knowledge, and remotely accessible frameworks, components and problems.
57
Corporate security solutions for BYOD
P. de las Cuevas,Antonio M. Mora,J. J. Merelo,Pedro A. Castillo,Pablo García-Sánchez,Antonio Fernández-Ares +5 more
TL;DR: A taxonomy to classify the features of BYOD systems is proposed and a novel, adaptive and free software system named MUSES (Multi-platform Usable Endpoint Security), able to securely manage BYOD environments is described, developed to cope with security issues with regard to enterprise security policies.
33
Artificial Neural Networks Design using Evolutionary Algorithms
Pedro A. Castillo,Maribel García Arenas,J. J. Castillo-Valdivieso,J. J. Merelo,Alberto Prieto,Gustavo Romero +5 more
- 01 Jan 2003
TL;DR: Although a great amount of algorithms have been devised to train the weights of a neural network for a fixed topology, most of them are hillclimbing procedures, which usually fall in a local optimum; that is why results obtained depend to a great extent on the learning parameters and the initial weights as well as on the network topology.
19
GPU Parallel Computation in Bioinspired Algorithms: A Review
Maribel García Arenas,Gustavo Romero,Antonio M. Mora,Pedro A. Castillo,J. J. Merelo +4 more
- 01 Jan 2012
TL;DR: This chapter reviews the use of GPUs to solve scientific problems, giving an overview of current software systems.
13
Evolving Evil: Optimizing Flocking Strategies through Genetic Algorithms for the Ghost Team in the Game of Ms. Pac-Man ⋆ (Published in EVOGames 2014 (EVOApplications))
Federico Liberatore,Antonio M. Mora,Pedro A. Castillo,J. J. Merelo +3 more
- 01 Jan 2014
TL;DR: In this paper, the authors present an applica- tion of genetic algorithms and flocking strategies to control the Ghost Team in the game Ms. Pac-Man, and optimize them for robustness with respect to the stochastic elements of the game and effectiveness against different possible opponents.