Javier Palanca

Dr. Javier Palanca

Universitat Politècnica de València, Spain
orcid

Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 April 2016
Verified
Book Chapter
Closed access
PDF file
EHEmilcy Hernández
Emilcy Hernández
VSVictor Sanchez-Anguix
Victor Sanchez-Anguix
Vicente JulianVicente Julian
Vicente Julian
JPJavier Palanca
Javier Palanca
Néstor Duque-MéndezNéstor Duque-Méndez
Néstor Duque-Méndez

28 September 2020 in IEEE Access
Verified
Journal Article
Open access
JPJavier Palanca
Javier Palanca
ATAndres Terrasa-Barrena
Andres Terrasa-Barrena
Vicente JulianVicente Julian
Vicente Julian
CCCarlos Carrascosa
Carlos Carrascosa
Although intelligent agent-based systems have existed for several years, the progression in terms of real applications or their integration in the industry have not yet reached the expected levels. During the last two decades, many agent platforms have appeared with the aim of simplifying the development of multi-agent systems. Some of these platforms have been designed for general purposes, while others have been oriented towards specific domains. However, the lack of standards and the complexity associated with supporting such systems, among other difficulties, have hampered their generalised use. This article looks in depth at the current situation of existing agent platforms, trying to analyse their current shortcomings and their expected needs in the near future. The goal of the paper is to identify possible lines of work and some of the most crucial aspects to be considered in order to popularize the application of agent technology as a dynamic and flexible solution to current problems. Moreover, the paper presents SPADE 3, a new version of the SPADE middleware, which has been totally redesigned in order to conform to the identified challenges. Finally, a case study is proposed to illustrate how SPADE 3 is able to fulfill these challenges.

5 March 2022 in Expert Systems with Applications
Verified
Journal Article
Closed access
JJJaume Jordán
Jaume Jordán
JPJavier Palanca
Javier Palanca
Pasqual MartíPasqual Martí
Pasqual Martí
Vicente JulianVicente Julian
Vicente Julian

1 May 2019 in Expert Systems with Applications
Verified
Journal Article
Closed access
HBHolger Billhardt
Holger Billhardt
AFAlberto Fernandez
Alberto Fernandez
SOSascha Ossowski
Sascha Ossowski
JPJavier Palanca
Javier Palanca
Javier BajoJavier Bajo
Javier Bajo

23 February 2018 in Applied Sciences
Verified
Journal Article
Open access
PDF file
JJJaume Jordán
Jaume Jordán
JPJavier Palanca
Javier Palanca
EVElena del Val-Noguera
Elena del Val-Noguera
Vicente JulianVicente Julian
Vicente Julian
Vicent BottiVicent Botti
Vicent Botti
One of the main current challenges of electric vehicles (EVs) is the creation of a reliable, accessible and comfortable charging infrastructure for citizens in order to enhance demand. In this paper, a multi-agent system (MAS) is proposed to facilitate the analysis of different placement configurations for EV charging stations. The proposed MAS integrates information from heterogeneous data sources as a starting point to characterize the areas where charging stations could potentially be placed. Through a genetic algorithm, the MAS is able to analyze a large number of possible configurations, taking into account a set of criteria to be optimized. Finally, the MAS returns a configuration with the areas of the city that are considered most appropriate for the establishment of charging stations according to the specified criteria.