CI-SUSTAIN
: Inteligencia Computacional Avanzada Para Alcanzar Objetivos De Desarrollo Sostenible
A Project coordinated by IIIA.
Principal investigator:
Collaborating organisations:
En 2015, todos los estados miembros de las Naciones Unidas adoptaron la Agenda 2030 para el desarrollo sostenible con el objetivo de alcanzar la paz y la prosperidad para todos los habitantes del planeta. La agenda establece 17 objetivos de desarrollo sostenible (SDGs). Estos objetivos instan a los países a tomar medidas para poner fin a la pobreza y otras privaciones por medio de estrategias que mejoren la salud y la educación, reduzcan la desigualdad y estimulen el crecimiento económico, todo ello sin impactar de forma negativa en el cambio climático y preservando nuestro planeta. Alcanzar estos objetivos es un reto para nuestra sociedad. Después de varios años trabajando en IA para el bien social, nuestro grupo ha identificado retos computacionales específicos, tanto en optimización como en aprendizaje automático, que surgen en áreas de aplicación relacionadas con objetivos de la Agenda 2030. Nuestro objetivo es hacer frente a estos desafíos avanzando el estado del arte en aspectos algorítmicos. Esto será necesario porque que los problemas de optimización que surgen en estas áreas de aplicación son problemas a gran escala que a menudo no pueden resolverse con los enfoques heurísticos y exactos disponibles en la actualidad. De hecho, planeamos avanzar el estado del arte a lo largo de las siguientes tres líneas. En primer lugar, contribuir a la adaptación de la metaheurística para su aplicación a problemas de gran escala. En segundo lugar, avanzar en la combinación de técnicas heurísticas con ideas algorítmicas de investigación de operaciones. En tercer lugar, contribuir en un campo de investigación novedoso como es el apoyo de algoritmos de optimización a las técnicas de aprendizaje automático. El objetivo del proyecto es demostrar que los avances computacionales logrados permiten mejorar con respecto al estado del arte en áreas de aplicación que están alineadas con algunos de los SDGs de la Agenda 2030 de la ONU para el Desarrollo Sostenible. En particular, nos ocuparemos de las siguientes áreas: (1) Intercambio de viajes entre pares (en relación con el SDG 11: Ciudades y comunidades sostenibles); (2) Formación de equipos (en relación con el SGD 4: Educación de calidad); (3) Aumento de la responsabilidad energética de los niños (en relación con el SGD 4: Educación de calidad); (4) Sistemas de salud inteligentes (en relación con el SGD 3: Salud y bienestar).
2024
Manel Rodríguez Soto,
Juan A. Rodríguez-Aguilar,
& Maite López-Sánchez
(2024).
An Analytical Study of Utility Functions in Multi-Objective Reinforcement Learning.
The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)
.
[BibTeX]
[PDF]
Nuria Correa,
Jesus Cerquides,
Rita Vassena,
Mina Popovic,
& Josep Lluis Arcos
(2024).
IDoser: Improving Individualized Dosing Policies with Clinical Practice and Machine Learning.
Expert Systems with Applications, 238, 121796.
https://doi.org/10.1016/j.eswa.2023.121796.
[BibTeX]
[PDF]
Annelies Raes,
Georgios Athanasiou,
Nima Azari-Dolatabad,
Hafez Sadeghi,
Sebastian Gonzalez Andueza,
Josep Lluis Arcos,
Jesus Cerquides,
Krishna Chaitanya Pavani,
Geert Opsomer,
Osvaldo Bogado Pascottini,
Katrien Smits,
Daniel Angel-Velez,
& Ann Van Soom
(2024).
Manual versus deep learning measurements to evaluate cumulus expansion of bovine oocytes and its relationship with embryo development in vitro.
Computers in Biology and Medicine, 168, 107785.
https://doi.org/10.1016/j.compbiomed.2023.107785.
[BibTeX]
[PDF]
Nuria Correa,
Jesus Cerquides,
Josep Lluis Arcos,
Rita Vassena,
& Mina Popovic
(2024).
Personalizing the First Dose of FSH for IVF/ICSI Patients through Machine Learning: A Non-Inferiority Study Protocol for a Multi-Center Randomized Controlled Trial.
Trials, 25, 38.
https://doi.org/10.1186/s13063-024-07907-2.
[BibTeX]
[PDF]
2023
Jordi Ganzer-Ripoll,
Natalia Criado,
Maite Lopez-Sanchez,
Simon Parsons,
& Juan A. Rodríguez-Aguilar
(2023).
A model to support collective reasoning: Formalization, analysis and computational assessment.
Journal of Artificial Intelligence Research.
[BibTeX]
[PDF]
Francisco Salas-Molina,
Juan A. Rodríguez-Aguilar,
& Montserrat Guillén
(2023).
A multidimensional review of the cash management problem.
Financial Innovation, 9.
[BibTeX]
[PDF]
Francisco Salas-Molina,
David Pla-Santamaria,
& Juan A. Rodríguez-Aguilar
(2023).
An analytic derivation of the efficient frontier in biobjective cash management and its implications for policies.
Annals of Operations Research.
[BibTeX]
[PDF]
Marc Serramia,
Maite López-Sánchez,
Stefano Moretti,
& Juan A. Rodríguez-Aguilar
(2023).
Building rankings encompassing multiple criteria to support qualitative decision-making.
Information Sciences, 631, 288-304.
[BibTeX]
[PDF]
Georgios Athanasiou,
Josep Lluis Arcos,
& Jesus Cerquides
(2023).
Enhancing Medical Image Segmentation: Ground Truth Optimization through Evaluating Uncertainty in Expert Annotations.
Mathematics, 11.
https://doi.org/10.3390/math11173771.
[BibTeX]
[PDF]
Borja Velasco-Regulez,
& Jesus Cerquides
(2023).
Hydranet: A Neural Network for the Estimation of Multi-Valued Treatment Effects.
Artificial Intelligence Research and Development (pp 16--27).
IOS Press.
https://doi.org/10.3233/FAIA230655.
[BibTeX]
[PDF]
Enrico Liscio,
Roger Lera-Leri,
Filippo Bistaffa,
Roel I. J. Dobbe,
Catholijn M. Jonker,
Maite López-Sánchez,
Juan A. Rodríguez-Aguilar,
& Pradeep K. Murukannaiah
(2023).
Inferring Values via Hybrid Intelligence.
Proceedings of the 2nd International Conference on Hybrid Human Artificial Intelligence (HHAI)
(pp. In press).
[BibTeX]
[PDF]
Hafiz Budi Firmansyah,
Jose Luis Fernandez-Marquez,
Jesus Cerquides,
& Giovanna Di Marzo Serugendo
(2023).
Single or Ensemble Model ? A Study on Social Media Images Classification in Disaster Response.
The 10th Multidisciplinary International Social Networks Conference
(pp. 48--54).
Association for Computing Machinery.
https://doi.org/10.1145/3624875.3624884.
[BibTeX]
[PDF]
Athina Georgara,
Raman Kazhamiakin,
Ornella Mich,
Alessio Palmero Approsio,
Jean-Christoph Pazzaglia,
Juan A. Rodríguez-Aguilar,
& Carles Sierra
(2023).
The AI4Citizen pilot: Pipelining AI-based technologies to support school-work alternation programmes.
Applied Intelligence.
https://doi.org/10.1007/s10489-023-04758-3.
[BibTeX]
[PDF]
Enrico Liscio,
Roger Xavier Lera Leri,
Filippo Bistaffa,
Roel I. J. Dobbe,
Catholijn M. Jonker,
Maite López-Sánchez,
Juan A. Rodríguez-Aguilar,
& Pradeep K. Murukannaiah
(2023).
Value Inference in Sociotechnical Systems.
Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS)
(pp. 1774-1780).
[BibTeX]
[PDF]
2022
Tomas Trescak,
Roger Xavier Lera Leri,
Filippo Bistaffa,
& Juan A. Rodríguez-Aguilar
(2022).
Agent-Assisted Life-Long Education and Learning.
Proceedings of the 21st International Conference on Autonomous Agents and MultiAgent Systems
.
International Foundation for Autonomous Agents and Multiagent Systems.
[BibTeX]
[PDF]
Athina Georgara,
Juan A. Rodríguez-Aguilar,
Carles Sierra,
Ornella Mich,
Raman Kazhamiakin,
Alessio P. Approsio,
& Jean-Christophe Pazzaglia
(2022).
An Anytime Heuristic Algorithm for Allocating Many Teams to Many Tasks.
Proceedings of the 21st International Conference on Autonomous Agents and MultiAgent Systems
.
International Foundation for Autonomous Agents and Multiagent Systems.
[BibTeX]
[PDF]
Eric Roselló-Marín,
Maite López-Sánchez,
Inmaculada Rodríguez Santiago,
Manel Rodríguez Soto,
& Juan A. Rodríguez-Aguilar
(2022).
An Ethical Conversational Agent to Respectfully Conduct In-Game Surveys.
Artificial Intelligence Research and Development (pp 335--344).
IOS Press.
[BibTeX]
[PDF]
Athina Georgara,
Juan A. Rodríguez-Aguilar,
& Carles Sierra
(2022).
Building Contrastive Explanations for Multi-Agent Team Formation.
Proceedings of the 21st International Conference on Autonomous Agents and MultiAgent Systems
.
International Foundation for Autonomous Agents and Multiagent Systems.
[BibTeX]
[PDF]
Georgios Athanasiou,
Jesus Cerquides,
Annelies Raes,
Nima Azari-Dolatabad,
Daniel Angel-Velez,
Ann Van Soom,
& Josep Lluis Arcos
(2022).
Detecting the Area of Bovine Cumulus Oocyte Complexes Using Deep Learning and Semantic Segmentation.
A. Cortés al. (Eds.),
Frontiers in Artificial Intelligence and Applications (pp 249-258).
IOS Press.
https://doi.org/10.3233/FAIA220346.
[BibTeX]
Filippo Bistaffa,
Georgios Chalkiadakis,
& Alessandro Farinelli
(2022).
Efficient Coalition Structure Generation via Approximately Equivalent Induced Subgraph Games.
IEEE Transactions on Cybernetics, 52, 5548-5558.
https://doi.org/10.1109/TCYB.2020.3040622.
[BibTeX]
[PDF]
Jerónimo Hernández-González,
Olga Valls,
Adrián Torres-Martín,
& Jesús Cerquides
(2022).
Modeling three sources of uncertainty in assisted reproductive technologies with probabilistic graphical models.
Computers in Biology and Medicine, 150, 106160.
https://doi.org/10.1016/j.compbiomed.2022.106160.
[BibTeX]
[PDF]
Nuria Correa,
Jesús Cerquides,
Josep Lluis Arcos,
& Rita Vassena
(2022).
Supporting first FSH dosage for ovarian stimulation with machine learning.
Reproductive Biomedicine Online.
https://doi.org/10.1016/j.rbmo.2022.06.010.
[BibTeX]
Roger Xavier Lera Leri,
Filippo Bistaffa,
Marc Serramia,
Maite López-Sánchez,
& Juan A. Rodríguez-Aguilar
(2022).
Towards Pluralistic Value Alignment: Aggregating Value Systems through ℓₚ-Regression.
Proceedings of the 21st International Conference on Autonomous Agents and MultiAgent Systems
.
International Foundation for Autonomous Agents and Multiagent Systems.
[BibTeX]
[PDF]
2021
Christian Blum,
& Gabriela Ochoa
(2021).
A comparative analysis of two matheuristics by means of merged local optima networks.
European Journal of Operational Research.
https://doi.org/10.1016/j.ejor.2020.08.008.
[BibTeX]
Teddy Nurcahyadi,
& Christian Blum
(2021).
Adding Negative Learning to Ant Colony Optimization:A Comprehensive Study.
Mathematics, 9.
https://doi.org/10.3390/math9040361.
[BibTeX]
[PDF]
Jesus Cerquides
(2021).
A First Approach to Closeness Distributions.
Mathematics, 9.
https://doi.org/10.3390/math9233112.
[BibTeX]
[PDF]
Marko Djukanovic,
Christoph Berger,
Günther R. Raidl,
& Christian Blum
(2021).
An A⁎ search algorithm for the constrained longest common subsequence problem.
Information Processing Letters, 166, 106041.
https://doi.org/10.1016/j.ipl.2020.106041.
[BibTeX]
[PDF]
Arthur Müller,
& Maite López-Sánchez
(2021).
Countering Negative Effects of Hate Speech in a Multi-Agent Society.
Artificial Intelligence Research and Development (pp 103--112).
IOS Press.
[BibTeX]
[PDF]
Manel Rodríguez Soto,
Maite López-Sánchez,
& Juan A. Rodríguez-Aguilar
(2021).
Guaranteeing the Learning of Ethical Behaviour through Multi-Objective Reinforcement Learning.
.
Adaptive and Learning Agents Workshop at AAMAS 2021 (ALA 2021).
[BibTeX]
[PDF]
Maite Lopez-Sanchez,
Marc Serramia,
& Juan A Rodríguez-Aguilar
(2021).
Improving on-line debates by aggregating citizen support.
Artificial Intelligence Research and Development.
IOS Press.
[BibTeX]
[PDF]
Núria Correa,
Rita Vassena,
Jesus Cerquides,
& Josep Lluis Arcos
(2021).
Limits of conventional Machine Learning methods to predict pregnancy and multiple pregnancy after embryo transfer.
Ada Valls, & Mateu Villaret (Eds.),
Frontiers in Artificial Intelligence and Applications (pp 245-253).
IOS Press.
[BibTeX]
Manel Rodríguez Soto,
Maite López-Sánchez,
& Juan A. Rodríguez-Aguilar
(2021).
Multi-Objective Reinforcement Learning for Designing Ethical Environments.
Proceedings of the 30th International Joint Conference on Artificial Intelligence, (IJCAI-21)
(pp. 545-551).
[BibTeX]
[PDF]
Maite López-Sánchez,
& Arthur Müller
(2021).
On Simulating the Propagation and Countermeasures of Hate Speech in Social Networks.
Applied Sciences, 11.
https://doi.org/10.3390/app112412003.
[BibTeX]
[PDF]
Borja Sánchez-López,
& Jesus Cerquides
(2021).
On the Convergence of Stochastic Process Convergence Proofs.
Mathematics, 9.
https://doi.org/10.3390/math9131470.
[BibTeX]
[PDF]
Marc Serramia,
Maite López-Sánchez,
Stefano Moretti,
& Juan A. Rodríguez-Aguilar
(2021).
On the dominant set selection problem and its application to value alignment.
Autonomous Agents and Multi-agent Systems, 35.
[BibTeX]
[PDF]
Jon Perez,
Jose Luis Flores,
Christian Blum,
Jesus Cerquides,
& Alex Abuin
(2021).
Optimization Techniques and Formal Verification for the Software Design of Boolean Algebra Based Safety-Critical Systems.
IEEE Transactions on Industrial Informatics, 1-1.
https://doi.org/10.1109/TII.2021.3074394.
[BibTeX]
Jesus Cerquides
(2021).
Parametrization invariant interpretation of priors and posteriors.
arXiv:2105.08304 [cs, math, stat].
http://arxiv.org/abs/2105.08304.
[BibTeX]
Christian Blum,
Marko Djukanovic,
Alberto Santini,
Hua Jiang,
Chu-Min Li,
Felip Manyà,
& Günter R. Raidl
(2021).
Solving Longest Common Subsequence Problems via a Transformation to the Maximum Clique Problem.
Computers & Operations Research, article number 105089.
https://doi.org/10.1016/j.cor.2020.105089.
[BibTeX]
Athina Georgara,
Juan A. Rodríguez-Aguilar,
& Carles Sierra
(2021).
Towards a Competence-Based Approach to Allocate Teams to Tasks.
Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems
(pp. 1504–1506).
International Foundation for Autonomous Agents and Multiagent Systems.
[BibTeX]
[PDF]
Adri{\'{a}}n Torres{-}Mart{í}n,
Jer{\'{o}}nimo Hern{\'{a}}ndez{-}Gonz{\'{a}}lez,
& Jes{\'{u}}s Cerquides
(2021).
Validation on Real Data of an Extended Embryo-Uterine Probabilistic Graphical Model for Embryo Selection.
Mateu Villaret, Teresa Alsinet, C{\\`{e}}sar Fern{\\'{a}}ndez, & A{\\"{\\i}}da Valls (Eds.),
Artificial Intelligence Research and Development - Proceedings of the 23rd International Conference of the Catalan Association for Artificial Intelligence, {CCIA}2021, Virtual Event, 20-22 October, 2021
(pp. 225--234).
{IOS}Press.
https://doi.org/10.3233/FAIA210139.
[BibTeX]
[PDF]
2020
Jordi Ganzer,
Natalia Criado,
Maite Lopez-Sanchez,
Simon Parsons,
& Juan A. Rodríguez-Aguilar
(2020).
A model to support collective reasoning: Formalization, analysis and computational assessment.
arXiv preprint arXiv:2007.06850.
[BibTeX]
[PDF]
Teddy Nurcahyadi,
& Christian Blum
(2020).
A New Approach for Making Use of Negative Learning in Ant Colony Optimization.
Marco Dorigo, Thomas Stützle, Maria J. Blesa, Christian Blum, Heiko Hamann, Mary Katherine Heinrich, & Volker Strobel (Eds.),
Swarm Intelligence
(pp. 16--28).
Springer International Publishing.
[BibTeX]
Jerónimo Hernández-González,
& Jesús Cerquides
(2020).
A Robust Solution to Variational Importance Sampling of Minimum Variance.
Entropy, 22, 1405.
https://doi.org/10.3390/e22121405.
[BibTeX]
[PDF]
Pedro Pinacho-Davidson,
& Christian Blum
(2020).
BARRAKUDA: A Hybrid Evolutionary Algorithm for Minimum Capacitated Dominating Set Problem.
Mathematics, 8.
https://doi.org/10.3390/math8111858.
[BibTeX]
[PDF]
Marko Djukanovic,
Christoph Berger,
Günther R. Raidl,
& Christian Blum
(2020).
On Solving a Generalized Constrained Longest Common Subsequence Problem.
Nicholas Olenev, Yuri Evtushenko, Michael Khachay, & Vlasta Malkova (Eds.),
Optimization and Applications
(pp. 55--70).
Springer International Publishing.
[BibTeX]
[PDF]
Matthias Horn,
Marko Djukanovic,
Christian Blum,
& Günther R. Raidl
(2020).
On the Use of Decision Diagrams for Finding Repetition-Free Longest Common Subsequences.
Nicholas Olenev, Yuri Evtushenko, Michael Khachay, & Vlasta Malkova (Eds.),
Optimization and Applications
(pp. 134--149).
Springer International Publishing.
[BibTeX]
[PDF]
Dhananjay Thiruvady,
Christian Blum,
& Andreas T. Ernst
(2020).
Solution Merging in Matheuristics for Resource Constrained Job Scheduling.
Algorithms, 13.
https://doi.org/10.3390/a13100256.
[BibTeX]
[PDF]
Josep Lluís Arcos
Scientific Researcher
Scientific Researcher
Inmaculada Rodríguez Santiago
Tenured University Lecturer
Tenured University Lecturer