General techniques: Soft Computing

(Data Mining, Intelligent Data Analysis, Optimization Techniques)

Evaluating the Multiple Offspring Sampling framework on complex continuous optimization functions

  • Memetic Computing (On-line version) (2013)
  • DOI: 10.1007/s12293-013-0120-80
  • A. LaTorre, S. Muelas, J.M. Peña

Distributed Estimation of Distribution Algorithms for Continuous Optimization: How does the Exchanged Information Influence their Behavior?

  • Information Sciences (On-line version) (2011)
  • DOI: 10.1016/j.ins.2011.11.030
  • S. Muelas, A. Mendiburu, A. LaTorre, J.M. Peña

A MOS-based Dynamic Memetic Differential Evolution Algorithm for Continuous Optimization A Scalability Test

  • SOFT COMPUTING - A FUSION OF FOUNDATIONS, METHODOLOGIES AND APPLICATIONS
  • Soft Computing Volume 15, Number 11 (2011), 2187-2199
  • DOI: 10.1007/s00500-010-0646-3
  • A. LaTorre, S. Muelas, J.M. Peña

Learning Hybridization Strategies in Evolutionary Algorithms

  • Intelligent Data Analysis Volume 14, Number 3 (2010), 333-354
  • DOI: 10.3233/IDA-2010-0424
  • A. LaTorre, J.M. Peña, S. Muelas, A.A. Freitas

A new initialization procedure for the distributed estimation of distribution algorithms

  • SOFT COMPUTING - A FUSION OF FOUNDATIONS, METHODOLOGIES AND APPLICATIONS
  • Soft Computing Volume 15, Number 4 (2010), 713-720
  • DOI: 10.1007/s00500-010-0603-1
  • S. Muelas, J.M. Peña, A. LaTorre, V. Robles

Feature selection for multi-label naive Bayes classification

  • Information Sciences Volume 179, Issue 19, 2009, 3218-3229
  • DOI: 10.1016/j.ins.2009.06.010
  • M-L Zhang, J.M. Peña, V. Robles

A Memetic Differential Evolution Algorithm for Continuous Optimization

  • International Conference on Intelligent Systems Design and Applications, 2009, 1080-1084
  • DOI: 10.1109/ISDA.2009.47
  • S. Muelas, A. LaTorre, J.M. Peña

Machine Learning to Analyze Migration Parameters in Parallel Genetic Algorithms

  • INNOVATIONS IN HYBRID INTELLIGENT SYSTEMS
  • Advances in Soft Computing, 2007, Volume 44, 199-206
  • DOI: 10.1007/978-3-540-74972-1_27
  • S. Muelas, J.M. Peña, V. Robles, A. LaTorre, P. de Miguel

Extending the GA-EDA Hybrid Algorithm to Study Diversification and Intensification in GAs and EDAs

  • ADVANCES IN INTELLIGENT DATA ANALYSIS VI
  • Lecture Notes in Computer Science, 2005, Volume 3646/2005, 741
  • DOI: 10.1007/11552253_31E
  • V. Robles, J.M. Peña, M.S. Perez, P. Herrero, O. Cubo

GA-EDA: Hybrid Evolutionary Algorithm using Genetic Algorithms and Estimation of Distribution Algorithms

  • INNOVATIONS IN APPLIED ARTIFICIAL INTELLIGENCE
  • Lecture Notes in Computer Science, 2004, Volume 3029/2004, 361-371
  • DOI: 10.1007/978-3-540-24677-0_38
  • J.M. Peña, V. Robles, P. Larrañaga, V. Herves, F. Rosales, M.S. Perez

Interval Estimation Naïve Bayes

  • ADVANCES IN INTELLIGENT DATA ANALYSIS V
  • Lecture Notes in Computer Science, 2003, Volume 2810/2003, 143-154
  • DOI: 10.1007/978-3-540-45231-7_14
  • V. Robles, P. Larrañaga, J.M. Peña, E. Menasalvas, M.S. Perez

Learning Semi Naïve Bayes Structures by Estimation of Distribution Algorithms

  • PROGRESS IN ARTIFICIAL INTELLIGENCE
  • Lecture Notes in Computer Science, 2003, Volume 2902/2003, 244-258
  • DOI: 10.1007/978-3-540-24580-3_31
  • V. Robles, P. Larrañaga, J.M. Peña, M.S. Perez, E. Menasalvas, V. Herves

Collaborative Filtering Using Interval Estimation Naïve-Bayes

  • ADVANCES IN WEB INTELLIGENCE
  • Lecture Notes in Computer Science, 2003, Volume 2663/2003, 954
  • DOI: 10.1007/3-540-44831-4_6
  • V. Robles, P. Larrañaga, J.M. Peña, O. Marbán, J. Crespo, M.S. Perez

A Framework to Integrate Business Goals in Web Usage Mining

  • ADVANCES IN WEB INTELLIGENCE
  • Lecture Notes in Computer Science, 2003, Volume 2663/2003, 955
  • DOI: 10.1007/3-540-44831-4_4
  • E. Hochsztain, S. Millan, B. Pardo, J.M. Peña, E. Menasalvas

Minimal Decision Rules Based on the Apriori Algorithm

  • SPECIAL ISSUE ON ROUGH SETS AND THEIR APPLICATIONS
  • International Journal of Applied Mathematics and Computer Science, 2001, Number 3, Volume 11/2001, 691-704
  • M.C. Fernandez, E. Menasalvas, O. Marban, J.M. Peña, S. Millan

Using the Apriori Algorithm to Improve Rough Sets Results

  • ROUGH SETS AND CURRENT TRENDS IN COMPUTING
  • Lecture Notes in Computer Science, 2001, Volume 2005/2001, 291-295
  • DOI: 10.1007/3-540-45554-X_35
  • M.C. Fernandez, E. Menasalvas, J.M. Peña, J.F. Martinez, S. Millan

DAMISYS an Overview

  • DATAWAREHOUSING AND KNOWLEDGE DISCOVERY
  • Lecture Notes in Computer Science, 1999, Volume 1676/1999, 802-803
  • DOI: 10.1007/3-540-48298-9_33
  • M.C. Fernandez, O. Delgado, J.I. Lopez, M.A. Luna, J.F. Martinez, B. Pardo, J.M. Peña

Rough Dependencies as a particular case of correlation: Application to the calculation of approximative reducts

  • PRINCIPLES OF DATA MINING AND KNOWLEDGE DISCOVERY
  • Lecture Notes in Computer Science, 1999, Volume 1704/1999, 335-340
  • DOI: 10.1007/978-3-540-48247-5_39
  • M.C. Fernandez, E. Menasalvas, J.M. Peña, S. Millan, E. Mesa

Integrating KDD algorithms and RDBMS code

  • ROUGH SETS AND CURRENT TRENDS IN COMPUTING
  • Lecture Notes in Computer Science, 1998, Volume 1424/1998, 210-213
  • DOI: 10.1007/3-540-69115-4_29
  • M.C. Fernandez, E. Menasalvas, J.M. Peña, B. Pardo

General techniques: Distributed Systems

(Parallel I/O, Distributed File Systems, System Architectures)

An agent architecture for managing data resources in a grid environment

  • Future Generation Computer Systems, Volume 25, Issue 7, July 2009, 747-755
  • DOI: 10.1016/j.future.2008.07.011
  • M.S. Perez, A. Sanchez, J. Abawajy, V. Robles, J.M. Peña

Design and implementation of a data mining grid-aware architecture

  • Future Generation Computer Systems, Volume 23, Issue 3, January 2007, 42-47
  • DOI: 10.1016/j.future.2006.04.008
  • M.S. Perez, A. Sanchez, V. Robles, P. Herrero, J.M. Peña

MAPFS: A flexible multiagent parallel filesystem for clusters

  • Future Generation Computer Systems, Volume 22, Issue 5, April 2006, 620-632
  • DOI: 10.1016/j.future.2005.09.006
  • M.S. Perez, J. Carretero, F. Garcia, J.M. Peña, V. Robles

A Parallel I/O Architecture based on Traditional and Distributed Servers

  • Information, Volume 9, Number 3, May 2006
  • ISSN 1343-450
  • M.S. Perez, A. Sanchez, V. Robles, J.M. Peña

A New Formalism for Dynamic Reconfiguration of Data Servers in a Cluster

  • DESIGN AND PERFORMANCE OF NETWORKS FOR SUPER-, CLUSTER-, AND GRID-COMPUTING
  • Journal of Parallel and Distributed Computing, 2005, Volume 65, Issue 10, 1134-1145
  • DOI: 10.1016/j.jpdc.2005.04.018
  • M.S. Perez, A. Sanchez, J.M. Peña, V. Robles

Adapting the Weka Data Mining Toolkit to a Grid Based Environment

  • ADVANCES IN WEB INTELLIGENCE
  • Lecture Notes in Computer Science, 2005, Volume 3528/2005, 819-820
  • DOI: 10.1007/11495772_77
  • M.S. Perez, A. Sanchez, P. Herrero, V. Robles, J.M. Peña

Optimizations Based on Hints in a Parallel File System

  • COMPUTATIONAL SCIENCE - ICCS 2004
  • Lecture Notes in Computer Science, 2004, Volume 3038/2004, 347-354
  • DOI: 10.1007/978-3-540-24688-6_47
  • M.S. Perez, A. Sanchez, V. Robles, J.M. Peña, F. Perez

Design and Evaluation of an Agent-Based Communication Model for a Parallel File System

  • COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2004
  • Lecture Notes in Computer Science, 2004, Volume 3044/2004, 87-96
  • DOI: 10.1007/978-3-540-24709-8_10
  • M.S. Perez, A. Sanchez, J. Abawajy, V. Robles, J.M. Peña

Bayesian Methods to Estimate Future Load in Web Farms

  • ADVANCES IN WEB INTELLIGENCE
  • Lecture Notes in Computer Science, 2004, Volume 3034/2004, 217-226
  • DOI: 10.1007/978-3-540-24681-7_24
  • J.M. Peña, V. Robles, O. Marban, M.S. Perez

Improving Distributed Data Mining Techniques by means of a Grid Infrastructure

  • ON THE MOVE TO MEANINGFUL INTERNET SYSTEMS 2004: OTM 2004 WORKSHOPS
  • Lecture Notes in Computer Science, 2004, Volume 3292/2004, 111-122
  • DOI: 10.1007/978-3-540-30470-8_29
  • A. Sanchez, J.M. Peña, M.S. Perez, V. Robles, P. Herrero

MAPFS-Grid: A Flexible Architecture for Data-Intensive Grid Applications

  • GRID COMPUTING
  • Lecture Notes in Computer Science, 2004, Volume 2970/2004, 111-118
  • DOI: 10.1007/978-3-540-24689-3_14
  • M.S. Perez, J. Carretero, F. Garcia, J.M. Peña, V. Robles

A Flexible Multiagent Parallel File System for Clusters

  • COMPUTATIONAL SCIENCE - ICCS 2003
  • Lecture Notes in Computer Science, 2003, Volume 2660/2003, 724
  • DOI: 10.1007/3-540-44864-0_26
  • M.S. Perez, J. Carretero, F. Garcia, J.M. Peña, V. Robles

MOIRAE - An Innovative Component Architecture with Distributed Control Features

  • COMPUTATIONAL SCIENCE - ICCS 2003
  • Lecture Notes in Computer Science, 2003, Volume 2658/2003, 682
  • DOI: 10.1007/3-540-44862-4_115
  • K. Leal, J. Herrera, J.M. Peña, E. Menasalvas

Parallel Data Mining Experimentation Using Flexible Configurations

  • ROUGH SETS AND CURRENT TRENDS IN COMPUTING
  • Lecture Notes in Computer Science, 2002, Volume 2475/2002, 949
  • DOI: 10.1007/3-540-45813-1_58
  • J.M. Peña, F.J. Crespo, E. Menasalvas, V. Robles

Bio- and Neuro-applications

(Genomics, Proteomics, Neuroinformatics)

A Machine Learning Method for the Prediction of Receptor Activation in the Simulation of Synapses

  • PLoS ONE, Volume 8, Issue 7, 2013, e68888
  • DOI: 10.1371/journal.pone.0068888
  • J. Montes, E. Gómez, A. Merchán-Pérez, J. DeFelipe, J.M. Peña

Segmentation of Neuronal Nuclei Based on Clump Splitting and a Two-step Binarization of Images

  • Expert Systems with Application, Volume 40, Issue 16, 2013, 6521-6530
  • DOI: 10.1016/j.eswa.2013.06.010
  • A. LaTorre, L. Alonso-Nanclares, S. Muelas, J.M. Peña, J. DeFelipe

A Model of the Spatially Dependent Mechanical Properties of the Axon During Its Growth

  • Computer Modeling in Engineering & Sciences(CMES) Volume 87, Number 5, 2012, 411-432
  • DOI: 10.3970/cmes.2012.087.411
  • J.A. Garcia, J.M. Peña, S. McHugh, A. Jerusalem

Scaling laws in bacterial genomes: Aside-effect of selection of mutational robustness?

  • FROM SMALL SCALE DYNAMICS TO UNDERSTANDING SYSTEMS BEHAVIOR
  • Biosystems, Volume 102, Issue 1, 2010, 32-40
  • DOI: 10.1016/j.biosystems.2010.07.009
  • G. Beslon, D. Parsons, Y. Sanchez-Dehesa, C. Knibbe, J.M. Peña

From Digital Genetics to Knowledge Discovery: Perspectives in Genetic Network Understanding

  • KNOWLEDGE DISCOVERY IN BIOINFORMATICS
  • Intelligent Data Analysis, Volume 14, Number 2, 2010, 173-191
  • DOI: 10.3233/IDA-2010-0415
  • G. Beslon, D. Parsons, J.M. Peña, C. Rigotti, Y. Sanchez-Dehesa

CliDaPa: A new approach to combining clinical data with DNA microarrays

  • KNOWLEDGE DISCOVERY IN BIOINFORMATICS
  • Intelligent Data Analysis, Volume 14, Number 2, 2010, 207-223
  • DOI: 10.3233/IDA-2010-0417
  • S. Gonzalez, L. Guerra, V. Robles, J.M. Peña, F. Famili

Modelling evolution of regulatory networks in artificial bacteria

  • Mathematical Modelling of Natural Phenomena, Volume 3, Number 2, 2008, 27-66
  • ISSN: 0973-5348
  • Y. Sanchez-Dehesa, D. Parsons, J.M. Peña, G. Beslon

Bayesian network multi-classifiers for protein secondary structure prediction

  • Artificial Intelligence in Medicine, Volume 31, Issue 2, 2004, 117-136
  • DOI: 10.1016/j.artmed.2004.01.009
  • V. Robles, P. Larrañaga, J.M. Peña, E. Menasalvas, M.S. Perez, V. Herves, A. Wasilewska

Parallel Stochastic Search for Protein Secondary Structure Prediction

  • PARALLEL PROCESSING AND APPLIED MATHEMATICS
  • Lecture Notes in Computer Science, 2004, Volume 3019/2004, 1162-1169
  • DOI: 10.1007/978-3-540-24669-5_149
  • V. Robles, M.S. Perez, V. Herves, J.M. Peña, P. Larrañaga

Engineering applications

(Aeronautics, Transport, Logistics)

A variable neighborhood search algorithm for the optimization of a dial-a-ride problem in a large city

  • Expert Systems with Applications, Volume 40, Issue 14, 15 October 2013, 5516-5531
  • DOI: 10.1016/j.eswa.2013.04.015,
  • S. Muelas, A. LaTorre, J.M. Peña

Application of Rough Sets Algorithms to Prediction of Aircraft Component Failure

  • ADVANCES IN INTELLIGENT DATA ANALYSIS
  • Lecture Notes in Computer Science, 1999, Volume 1642/1999, 473-484
  • DOI: 10.1007/3-540-48412-4_40
  • J.M. Peña, S. Letourneau, F. Famili

Video games

(Content Generation, Emotional Models)

Soft computing for content generation: Trading market in a basketball management video game

  • IEEE Conference on Computational Intelligence in Games 2013, 41-48
  • DOI: XXXX
  • J.M. Peña, E. Menasalvas, S. Muelas, A. LaTorre, L. Peña, S. Ossowski

Learning and evolving combat game controllers

  • IEEE Conference on Computational Intelligence in Games 2012, 195-202
  • DOI: 10.1109/CIG.2012.6374156
  • L. Peña, S. Ossowski, J.M. Peña, S.M. Lucas

EEP - A lightweight emotional model: Application to RPG video game characters

  • IEEE Conference on Computational Intelligence in Games 2011, 142-149
  • DOI: 10.1109/CIG.2011.6032000
  • L. Peña, S. Ossowski, J.M. Peña, J.A. Sanchez

Representing Emotion and Mood States for Virtual Agents

  • MULTIAGENT SYSTEM TECHNOLOGIES
  • Lecture Notes in Computer Science, 2011, Volume 6973/2011, 181-188
  • DOI: 10.1007/978-3-642-24603-6_19
  • L. Peña, J.M. Peña, S. Ossowski

Evolving Q-learners for stochastic games: Study on video game agent controllers

  • World Automation Congress (WAC), 2010, 1-6
  • L. Peña, J.M. Peña, S. Ossowski, P. Herrero

vBattle: A new Framework to Simulate Medium-Scale Battles in Individual-per-Individual Basis

  • IEEE Conference on Computational Intelligence in Games 2009, 61-68
  • DOI: 10.1109/CIG.2009.5286492
  • L. Peña, S. Ossowski, J.M. Peña

Tentative Exploration on Reinforcement Learning Algorithms for Stochastic Rewards

  • HYBRID ARTIFICIAL INTELLIGENCE SYSTEMS
  • Lecture Notes in Computer Science, 2009, Volume 5572/2009, 336-343
  • DOI: 10.1007/978-3-642-02319-4_40
  • L. Peña, A. LaTorre, J.M. Peña, S. Ossowski