Fernando Fernández
Full Professor
About Me
I am a Full Professor at Universidad Carlos III de Madrid, Spain. I work at the Computer Science and Engineering Department, and I am the Head of the Planning & Learning Group (PLG). I am also co-founder and CSO of Inrobocs Social Robotics, a spin-off from UC3M.
Short bio
Fernando Fernández is a Full Professor of the Computer Science & Engineering Department at Universidad Carlos III de Madrid, and Founder of Inrobics Social Robotics. He received his Ph.D. degree in Computer Science from University Carlos III of Madrid (UC3M) in 2003. He received his B.Sc. in 1999 from UC3M, also in Computer Science. In the fall of 2000, Fernando was a visiting student at the Center for Engineering Science Advanced Research at Oak Ridge National Laboratory. He was also a postdoctoral fellow at the Computer Science Department of Carnegie Mellon University since October 2004 until December 2005 and visitor of the Robotics Institute of the University of Texas at Austin since July 2022 to June 2023. He is the recipient of a pre-doctoral FPU fellowship award from Spanish Ministry of Education (MEC), a Doctoral Prize from UC3M, and a MEC-Fulbright postdoctoral Fellowship as well as the 2020 and 2021 JPMorgan AI Research Awards. He has more than 80 journal and conference papers, mainly in the field of machine learning, automated planning and robotics. He is interested in intelligent systems that operate in continuous and stochastic domains. He is the Director of the Planning and Learning Group of the Computer Science Department at UC3M. He is also co-founder and CSO of Inrobocs Social Robotics, where social assistive robots are deployed in rehabilitation hospitals.
Publications
2026
Óscar Fernández Vicente, Javier García and Fernando Fernández.
Optimizing market-making strategies: A multi-objective reinforcement learning approach with pareto fronts.
Expert Systems with Applications 295. 2026.
citation
2025
Javier Moralejo-Piñas, Francisco Martínez-Gil, María Soriano Santacruz and Fernando Fernández.
Electric vehicle market dynamics: A multi-agent approach to policy, infrastructure, and consumer behavior.
Energy Policy 206, pp. 114800. 2025.
paper citationEnrique Mateos-Melero, Miguel Iglesias Alcázar, Raquel Fuentetaja and Fernando Fernández.
Dataset Reduction for Offline Reinforcement Learning using Genetic Algorithms with Image-Based Heuristics.
In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 416–424. 2025.
paper citationEnrique Mateos-Melero, Javier Moralejo-Piñas, Francisco Martínez-Gil, María Soriano and Fernando Fernández.
Evolutionary Optimization of the Gas/Charging Stations Topology for the Electric Vehicle Market.
In Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 867–870. 2025.
paper citationEnrique Mateos-Melero, Javier Moralejo-Piñas, Angela Durán-Pinto, Francisco Martínez-Gil, María Soriano and Fernando Fernández.
Where is the Nearest EV Charging Station? Evolutionary Optimization of the Gas/charging Stations Topology.
In Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems, pp. 2666–2668. 2025.
paper citationAlba Gragera, Angel Garcia-Olaya and Fernando Fernández.
On the Combination of Classical Knowledge Engineering Tools and LLMs to Build Automated Planning Models.
International journal of software engineering and knowledge engineering 35. 2025.
citationAlba Gragera, Carmen Díaz-De-Mera, Juan Pedro Bandera, Angel Garcia-Olaya and Fernando Fernández.
Towards a No Code Deployment of Social Robotics Use Cases.
Expert Systems 42, pp. e70038. 2025.
paper citationÓscar Fernández Vicente, Javier García and Fernando Fernández.
Policy weighting via discounted Thomson sampling for non-stationary market-making.
Artificial Intelligence Review 58. 2025.
citationAlba Gragera, Raquel Fuentetaja, Angel García-Olaya and Fernando Fernández.
On the Gains from Using Action Observations in Domain Repair.
In Proceedings of the Thirty-Fifth International Conference on Automated Planning and Scheduling (ICAPS 2025), pp. 343 – 347. 2025.
citation
2024
Enrique Mateos-Melero, Miguel Iglesias Alcázar, Raquel Fuentetaja, Peter Stone and Fernando Fernández.
Image-based Dataset Representations for Predicting Learning Performance in Offline RL.
In . 2024.
paper citationJose Carlos Pulido, Raquel Fuentetaja, Enrique García, Melania García, Vanesa Abuín, Jose Carlos González, Ana Iglesias and Fernando Fernández.
A gamified social robotics platform for intensive therapies in neurorehabilitation.
Intelligent Service Robotics 17, pp. 419 – 443. 2024.
paper citationRubén Majadas, Javier García and Fernando Fernández.
Clustering-based attack detection for adversarial reinforcement learning.
Applied Intelligence 54, pp. 2631 – 2647. 2024.
paper citationAna Iglesias, Fernando Fernández, Jose Carlos Pulido, Carmen Diaz, Malak Qbilat and Amy Pavel.
Accessibility Evaluation of an Assistive Social Robotic Platform for Rehabilitation and Its Improvement by Means of Haptic Devices.
In Procedia Computer Science, pp. 1516 – 1523. 2024.
citation
2023
Jose Luis Pérez, Javier Corrochano, Javier García, Rubén Majadas, Cristina Ibañez-Llano, Sergio Pérez and Fernando Fernández.
DISCRETE UNCERTAINTY QUANTIFICATION FOR OFFLINE REINFORCEMENT LEARNING.
Journal of Artificial Intelligence and Soft Computing Research 13, pp. 273 – 287. 2023.
paper citationÓscar Fernández Vicente, Fernando Fernández and Javier García.
Automated market maker inventory management with deep reinforcement learning.
Applied Intelligence 53, pp. 22249 – 22266. 2023.
paper citationAlba Gragera, Raquel Fuentetaja, Angel García-Olaya and Fernando Fernández.
A Planning Approach to Repair Domains with Incomplete Action Effects.
In Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling (ICAPS 2023), pp. 153 – 161. 2023.
citation
2022
Alba Gragera, Carmen Díaz-De-Mera, Alberto Tudela, Alejandro Cruces, Fernando Fernández and Angel Garcia-Olaya.
Towards an Easy Use Case Implementation in Social Robotics.
, pp. 9. 2022.
paper citationJavier García, Álvaro Visús and Fernando Fernández.
A taxonomy for similarity metrics between Markov decision processes.
Machine Learning 111, pp. 4217 – 4247. 2022.
paper citationDimitri Voilmy, Karine Lan Hing Ting, Ana Iglesias, Rebeca Marfil, Juan Pedro Bandera, Fernando Fernández and Quitterie de Roll.
Robotic geriatric assistant: A pilot assessment in a real-world hospital.
Unknown bibtex type book 2022.
citation
2021
Óscar Fernández Vicente, Fernando Fernández and Francisco Javier García Polo.
Deep Q-learning market makers in a multi-agent simulated stock market.
In ICAIF 2021 - 2nd ACM International Conference on AI in Finance. 2021.
citationAna Iglesias, Javier García, Angel García-Olaya, Raquel Fuentetaja, Fernando Fernández, Adrian Romero-Garces, Rebeca Marfil, Antonio Bandera, Karine Lan Hing Ting, Dimitri Voilmy, Alvaro Duenas and Cristina Suarez-Mejias.
Extending the Evaluation of Social Assistive Robots with Accessibility Indicators: The AUSUS Evaluation Framework.
IEEE Transactions on Human-Machine Systems 51, pp. 601 – 612. 2021.
citationDaniel Fernandez, Fernando Fernández and Javier García.
Probabilistic Multi-knowledge Transfer in Reinforcement Learning.
In Proceedings - 20th IEEE International Conference on Machine Learning and Applications, ICMLA 2021, pp. 471 – 476. 2021.
citation
2020
Javier García, Rubén Majadas and Fernando Fernández.
Learning adversarial attack policies through multi-objective reinforcement learning.
Engineering Applications of Artificial Intelligence 96. 2020.
citationRaquel Fuentetaja, Angel García-Olaya, Javier García, Jose Carlos González and Fernando Fernández.
An automated planning model for hri: Use cases on social assistive robotics.
Sensors 20, pp. 1 – 19. 2020.
citationAdrián Gallego, Jose Carlos Pulido, Jose Carlos González and Fernando Fernández.
Design of a Robotic as a Service Platform to Perform Rehabilitation Therapies.
Advances in Intelligent Systems and Computing 1093 AISC, pp. 681 – 692. 2020.
citationAlba Gragera, Alba María García and Fernando Fernández.
A Modelling and Formalisation Tool for Use Case Design in Social Autonomous Robotics.
Advances in Intelligent Systems and Computing 1093 AISC, pp. 656 – 667. 2020.
citation
2019
Mlsra Turp, Jose Carlos González, Jose Carlos Pulido and Fernando Fernández.
Developing a robot-guided interactive simon game for physical and cognitive training.
International Journal of Humanoid Robotics 16. 2019.
citationJavier García and Fernando Fernández.
Probabilistic policy reuse for safe reinforcement learning.
ACM Transactions on Autonomous and Adaptive Systems 13. 2019.
citationElena Krasheninnikova, Javier García, Roberto Maestre and Fernando Fernández.
Reinforcement learning for pricing strategy optimization in the insurance industry.
Engineering Applications of Artificial Intelligence 80, pp. 8 – 19. 2019.
citationJose Carlos Pulido, Cristina Suarez-Mejias, Jose Carlos González, Alvaro Duenas Ruiz, Patricia Ferrand Ferri, Maria Encarnacion Martinez Sahuquillo, Carmen Echevarria Ruiz De Vargas, Pedro Infante-Cossio, Carlos Luis Parra Calderon and Fernando Fernández.
A Socially Assistive Robotic Platform for Upper-Limb Rehabilitation: A Longitudinal Study with Pediatric Patients.
IEEE Robotics and Automation Magazine 26, pp. 24 – 39. 2019.
citationAngel García-Olaya, Raquel Fuentetaja, Javier García, Jose Carlos González and Fernando Fernández.
Challenges on the Application of Automated Planning for Comprehensive Geriatric Assessment Using an Autonomous Social Robot.
Advances in Intelligent Systems and Computing 855, pp. 179 – 194. 2019.
citation
2018
Francisco Martinez-Gil, Miguel Lozano, Ignacio García-Fernández and Fernando Fernández.
Modeling, evaluation, and scale on artificial pedestrians: A literature review.
ACM Computing Surveys 50. 2018.
citationMoisés Martínez, Javier García and Fernando Fernández.
On-Line Case-Based Policy Learning for Automated Planning in Probabilistic Environments.
International Journal of Information Technology and Decision Making 17, pp. 763 – 800. 2018.
citationDimitri Voilmy, Cristina Suárez, Adrian Romero-Garcés, Cristian Reuther, Jose Carlos Pulido, Rebeca Marfil, Luis J. Manso, Karine Lan Hing Ting, Ana Iglesias, Jose Carlos González, Javier García, Angel García-Olaya, Raquel Fuentetaja, Fernando Fernández, Alvaro Dueñas, Luis Vicente Calderita, Pablo Bustos, T. Barile, Juan Pedro Bandera and Antonio Bandera.
CLARC: A cognitive robot for helping geriatric doctors in real scenarios.
Advances in Intelligent Systems and Computing 693, pp. 403 – 414. 2018.
citationEnrique García Estévez, Irene Díaz Portales, Jose Carlos Pulido, Raquel Fuentetaja and Fernando Fernández.
Enhancing a robotic rehabilitation model for hand-arm bimanual intensive therapy.
Advances in Intelligent Systems and Computing 693, pp. 379 – 390. 2018.
citation
2017
Jose Carlos Pulido, Jose Carlos González, Cristina Suárez-Mejías, Antonio Bandera, Pablo Bustos and Fernando Fernández.
Evaluating the Child–Robot Interaction of the NAOTherapist Platform in Pediatric Rehabilitation.
International Journal of Social Robotics 9, pp. 343 – 358. 2017.
paper citationJose Carlos González, Jose Carlos Pulido and Fernando Fernández.
A three-layer planning architecture for the autonomous control of rehabilitation therapies based on social robots.
Cognitive Systems Research 43, pp. 232 – 249. 2017.
citationFrancisco Martinez-Gil, Miguel Lozano and Fernando Fernández.
Emergent behaviors and scalability for multi-agent reinforcement learning-based pedestrian models.
Simulation Modelling Practice and Theory 74, pp. 117 – 133. 2017.
citationTomás De La Rosa, Isabel Cenamor and Fernando Fernández.
Performance modelling of planners from homogeneous problem sets.
In Proceedings of the Twenty-Seventh International Conference on Automated Planning and Scheduling (ICAPS 2017), pp. 425 – 433. 2017.
citation
2016
Moisés Martínez, Fernando Fernández and Daniel Borrajo.
Planning and execution through variable resolution planning.
Robotics and Autonomous Systems 83, pp. 214 – 230. 2016.
citationIsabel Cenamor, Tomás De La Rosa and Fernando Fernández.
The IBaCoP planning system: Instance-based configured portfolios.
Journal of Artificial Intelligence Research 56, pp. 657 – 691. 2016.
citation
2015
Javier García and Fernando Fernández.
A comprehensive survey on safe reinforcement learning.
Journal of Machine Learning Research 16, pp. 1437 – 1480. 2015.
citationFrancisco Martinez-Gil, Miguel Lozano and Fernando Fernández.
Strategies for simulating pedestrian navigation with multiple reinforcement learning agents.
Autonomous Agents and Multi-Agent Systems 29, pp. 98 – 130. 2015.
citationAlejandro Martín, José C. González, José C. Pulido, Angel García-Olaya, Fernando Fernández and Cristina Suárez.
Therapy Monitoring and Patient Evaluation with Social Robots.
In ACM International Conference Proceeding Series, pp. 152 – 155. 2015.
citationFrancisco Martinez-Gil, Miguel Lozano and Fernando Fernández.
Emergent collective behaviors in a multi-agent reinforcement learning pedestrian simulation: A case study.
Lecture Notes in Computer Science 9002, pp. 228 – 238. 2015.
citation
2014
Francisco Martinez-Gil, Miguel Lozano and Fernando Fernández.
MARL-Ped: A multi-agent reinforcement learning based framework to simulate pedestrian groups.
Simulation Modelling Practice and Theory 47, pp. 259 – 275. 2014.
citationLuis Vicente Calderita, Luis J. Manso, Pablo Bustos, Cristina Suárez-Mejías, Fernando Fernández and Antonio Bandera.
Therapist:towards an autonomous socially interactive robot for motor and neurorehabilitation therapies for children.
JMIR Rehabilitation and Assistive Technologies 1. 2014.
citation
2013
Victor Gonzalez-Pacheco, Maria Malfaz, Fernando Fernández and Miguel A. Salichs.
Teaching human poses interactively to a social robot.
Sensors 13, pp. 12406 – 12430. 2013.
citationSergio Jiménez, Fernando Fernández and Daniel Borrajo.
Integrating planning, execution, and learning to improve plan execution.
Computational Intelligence 29, pp. 1 – 36. 2013.
citationSusana Fernández, Tomás De La Rosa, Fernando Fernández, Rubén Suárez, Javier Ortiz, Daniel Borrajo and David Manzano.
Using automated planning for improving data mining processes.
The Knowledge Engineering Review 28, pp. 157 – 173. 2013.
citationAntonio Jesus Palomino, Angel García-Olaya, Fernando Fernández and Juan Pedro Bandera.
From perception to action and vice versa: A new architecture showing how perception and action can modulate each other simultaneously.
In 2013 European Conference on Mobile Robots, ECMR 2013 - Conference Proceedings, pp. 268 – 273. 2013.
citationFernando Fernández and Manuela Veloso.
Learning domain structure through probabilistic policy reuse in reinforcement learning.
Progress in Artificial Intelligence 2, pp. 13 – 27. 2013.
paper citation
2012
Sergio Jiménez, Tomás De La Rosa, Susana Fernández, Fernando Fernández and Daniel Borrajo.
A review of machine learning for automated planning.
The Knowledge Engineering Review 27, pp. 433 – 467. 2012.
citationJavier García and Fernando Fernández.
Safe exploration of state and action spaces in reinforcement learning.
Journal of Artificial Intelligence Research 45, pp. 515 – 564. 2012.
citationFrancisco Martinez-Gil, Miguel Lozano and Fernando Fernández.
Multi-agent reinforcement learning for simulating pedestrian navigation.
Lecture Notes in Computer Science 7113 LNAI, pp. 54 – 69. 2012.
citationFrancisco Martinez-Gil, Miguel Lozano and Fernando Fernández.
Calibrating a motion model based on reinforcement learning for pedestrian simulation.
Lecture Notes in Computer Science 7660 LNCS, pp. 302 – 313. 2012.
citationJavier González-Quijano, Mohamed Abderrahim, Fernando Fernández and Choukri Bensalah.
A kinodynamic planning-learning algorithm for complex robot motor control.
In 2012 IEEE Conference on Evolving and Adaptive Intelligent Systems, EAIS 2012 - Proceedings, pp. 80 – 83. 2012.
citationJosé Eloy Flórez, Javier Carbó and Fernando Fernández.
A meta-tool to support the development of knowledge engineering methodologies and projects.
International Journal of Software Engineering and Knowledge Engineering 22, pp. 1055 – 1083. 2012.
citationJavier García, Fernando Borrajo and Fernando Fernández.
Reinforcement learning for decision-making in a business simulator.
International Journal of Information Technology and Decision Making 11, pp. 935 – 960. 2012.
citationRocío García-Durán, Fernando Fernández and Daniel Borrajo.
A prototype-based method for classification with time constraints: A case study on automated planning.
Pattern Analysis and Applications 15, pp. 261 – 277. 2012.
citation
2011
Ezequiel Quintero, Vidal Alcázar, Daniel Borrajo, Juan Fdez-Olivares, Fernando Fernández, Angel García-Olaya, César Guzmán, Eva Onaindía and David Prior.
Autonomous mobile robot control and learning with the PELEA architecture.
In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2011), pp. 51 – 56. 2011.
citationEzequiel Quintero, Angel García-Olaya, Daniel Borrajo and Fernando Fernández.
Control of autonomous mobile robots with automated planning.
Journal of Physical Agents 5, pp. 3 – 13. 2011.
citationFernando Borrajo, Yolanda Bueno, Fernando Fernández, Javier García, Isidro de Pablo, Ismael Sagredo and Begoña Santos.
Business simulators for business education and research: SIMBA experience.
Unknown bibtex type book 2011.
citationRubén Suárez, Rocío García-Durán and Fernando Fernández.
A similarity function with local feature weighting for structured data.
In ESANN 2011 - 19th European Symposium on Artificial Neural Networks, pp. 369 – 374. 2011.
citationJavier García, Iván López-Bueno, Fernando Fernández and Daniel Borrajo.
A comparative study of discretization approaches for state space generalization in the keepaway soccer task.
Unknown bibtex type book 2011.
citation
2010
Fernando Fernández, Javier García and Manuela Veloso.
Probabilistic Policy Reuse for inter-task transfer learning.
Robotics and Autonomous Systems 58, pp. 866 – 871. 2010.
citationFernando Borrajo, Yolanda Bueno, Isidro de Pablo, Begoña Santos, Fernando Fernández, Javier García and Ismael Sagredo.
SIMBA: A simulator for business education and research.
Decision Support Systems 48, pp. 498 – 506. 2010.
citationJavier García, Fernando Fernández and Fernando Borrajo.
Learning virtual agents for decision-making in business simulators.
In CEUR Workshop Proceedings. 2010.
citationFrancisco Martinez-Gil, Fernando Barber, Miguel Lozano, Francisco Grimaldo and Fernando Fernández.
A reinforcement learning approach for multiagent navigation.
In ICAART 2010 - 2nd International Conference on Agents and Artificial Intelligence, Proceedings, pp. 607 – 610. 2010.
citationFernando Borrajo, Yolanda Bueno, Fernando Fernández, Javier García, Isidro de Pablo, Ismael Sagredo and Begoña Santos.
Business simulation in business education.
Unknown bibtex type book 2010.
citation
2009
Fernando Fernández, Daniel Borrajo, Susana Fernández and David Manzano.
Assisting data mining through automated planning.
Lecture Notes in Computer Science 5632 LNAI, pp. 760 – 774. 2009.
citationIván López-Bueno, Javier García and Fernando Fernández.
Two steps reinforcement learning in continuous reinforcement learning tasks.
Lecture Notes in Computer Science 5517 LNCS, pp. 577 – 584. 2009.
citationAna Iglesias, Paloma Martínez, Ricardo Aler and Fernando Fernández.
Reinforcement learning of pedagogical policies in adaptive and intelligent educational systems.
Knowledge-Based Systems 22, pp. 266 – 270. 2009.
citationAna Iglesias, Paloma Martínez, Ricardo Aler and Fernando Fernández.
Learning teaching strategies in an Adaptive and Intelligent Educational System through Reinforcement Learning.
Applied Intelligence 31, pp. 89 – 106. 2009.
citation
2008
Rocío García-Durán, Fernando Fernández and Daniel Borrajo.
Learning and transferring relational instance-based policies.
In Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (AAAI 2008), pp. 19 – 24. 2008.
citationFernando Fernández and Pedro Isasi.
Local feature weighting in nearest prototype classification.
IEEE Transactions on Neural Networks 19, pp. 40 – 53. 2008.
citationSergio Jiménez, Fernando Fernández and Daniel Borrajo.
The PELA Architecture: Integrating Planning and Learning to Improve Execution.
In Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (AAAI 2008), pp. 1294 – 1299. 2008.
citationRocío García-Durán, Fernando Fernández and Daniel Borrajo.
Prototypes based relational learning.
Lecture Notes in Computer Science 5253 LNAI, pp. 130 – 143. 2008.
citationFernando Fernández and Pedro Isasi.
Nearest prototype classification of noisy data.
Artificial Intelligence Review 30, pp. 53 – 66. 2008.
citationFernando Fernández and Daniel Borrajo.
Two steps reinforcement learning.
International Journal of Intelligent Systems 23, pp. 213 – 245. 2008.
citation
2007
Rocío García-Durán, Fernando Fernández and Daniel Borrajo.
Combining macro-operators with control knowledge.
Lecture Notes in Computer Science 4455 LNAI, pp. 229 – 243. 2007.
citation
2006
David Camacho, Fernando Fernández and Miguel A. Rodelgo.
Roboskeleton: An architecture for coordinating robot soccer agents.
Engineering Applications of Artificial Intelligence 19, pp. 179 – 188. 2006.
citationFernando Fernández and Manuela Veloso.
Probabilistic policy reuse in a reinforcement learning agent.
In Proceedings of the International Conference on Autonomous Agents, pp. 720 – 727. 2006.
citationFernando Fernández and Manuela Veloso.
Reusing and building a policy library.
In Proceedings of the Sixteenth International Conference on Automated Planning and Scheduling (ICAPS 2006), pp. 378 – 381. 2006.
citation
2005
Fernando Fernández, Daniel Borrajo and Lynne E. Parker.
A reinforcement learning algorithm in cooperative multi-robot domains.
Journal of Intelligent and Robotic Systems: Theory and Applications 43, pp. 161 – 174. 2005.
citationSergio Jiménez, Fernando Fernández and Daniel Borrajo.
Machine learning of plan robustness knowledge about instances.
Lecture Notes in Computer Science 3720 LNAI, pp. 609 – 616. 2005.
paper citation
2004
Fernando Fernández and Pedro Isasi.
Evolutionary design of nearest prototype classifiers.
Journal of Heuristics 10, pp. 431 – 454. 2004.
citationAna Iglesias, Paloma Martínez, Ricardo Aler and Fernando Fernández.
Learning content sequencing in an educational environment according to student needs.
In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), pp. 454 – 463. 2004.
citation
2003
Agapito Ledezma, Fernando Fernández and Ricardo Aler.
From continuous behaviour to discrete knowledge.
Lecture Notes in Computer Science 2687, pp. 217 – 224. 2003.
citationAna Iglesias, Paloma Martinez and Fernando Fernández.
Navigating through the RLATES interface: A web-based adaptive and intelligent educational system.
Lecture Notes in Computer Science 2889, pp. 175 – 184. 2003.
citation
2002
Fernando Fernández and Pedro Isasi.
Automatic finding of good classifiers following a biologically inspired metaphor.
Computing and Informatics 21, pp. 205 – 220. 2002.
citationAna Iglesias, Paloma Martínez, Dolores Cuadra, Elena Castro and Fernando Fernández.
Learning to teach database design by trial and error.
In ICEIS 2002 - Proceedings of the 4th International Conference on Enterprise Information Systems, pp. 500 – 505. 2002.
citation
2000
Fernando Fernández and Daniel Borrajo.
VQQL. Applying vector quantization to reinforcement learning.
Lecture Notes in Computer Science 1856, pp. 292 – 303. 2000.
citation
1999
Belen Ruiz-Mezcua, Dolores Garcia-Plaza, Cristina Fernandez, Paloma Domingo-Garcia and Fernando Fernández.
Biometrics verification in a real environment.
In IEEE Annual International Carnahan Conference on Security Technology, Proceedings, pp. 243 – 246. 1999.
citation