TAILOR
TAILOR

TAILOR
TAILOR
 : 
Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization
Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization

A Project coordinated by IIIA.

Web page:

Principal investigator: 

Collaborating organisations:

LINKOPINGS UNIVERSITET
CONSIGLIO NAZIONALE DELLE RICERCHE
IINSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
UNIVERSITY COLLEGE CORK - NATIONAL UNIVERSITY OF IRELAND, CORK
KATHOLIEKE UNIVERSITEIT LEUVEN
...

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LINKOPINGS UNIVERSITET
CONSIGLIO NAZIONALE DELLE RICERCHE
IINSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE
UNIVERSITY COLLEGE CORK - NATIONAL UNIVERSITY OF IRELAND, CORK
KATHOLIEKE UNIVERSITEIT LEUVEN
UNIVERSITA DEGLI STUDI DI ROMA LA SAPIENZA
UNIVERSITEIT LEIDEN
INSTITUTO SUPERIOR TECNICO
UNIVERSIDAD POMPEU FABRA
ALMA MATER STUDIORUM - UNIVERSITA DI BOLOGNA
BAR ILAN UNIVERSITY
TECHNISCHE UNIVERSITEIT EINDHOVEN
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
INSTITUT JOZEF STEFAN
TECHNISCHE UNIVERSITAT DARMSTADT
UNIVERSITY OF BRISTOL
ALBERT-LUDWIGS-UNIVERSITAET FREIBURG
THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
University of Trento
VRIJE UNIVERSITEIT BRUSSEL
UNIVERZITA KARLOVA
COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES
UNIVERSITE D'ARTOIS
CESKE VYSOKE UCENI TECHNICKE V PRAZE
TECHNISCHE UNIVERSITEIT DELFT
DEUTSCHES FORSCHUNGSZENTRUM FUR KUNSTLICHE INTELLIGENZ GMBH
ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
FONDAZIONE BRUNO KESSLER
FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.
TECHNISCHE UNIVERSITAET GRAZ
AGENCIA ESTATAL CONSEJO SUPERIOR DEINVESTIGACIONES CIENTIFICAS
UNIVERSITY OF LANCASTER
ETHNIKO KAI KAPODISTRIAKO PANEPISTIMIO ATHINON
UNIVERSIDAD DE MALAGA
POLITECHNIKA POZNANSKA
RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN
CONSORZIO INTERUNIVERSITARIO NAZIONALE PER L'INFORMATICA
Slovenské centrum pre výskum umelej inteligencie - Slovak AI
NEDERLANDSE ORGANISATIE VOOR TOEGEPAST NATUURWETENSCHAPPELIJK ONDERZOEK TNO
UNIVERSITA DI PISA
UNIVERSITE GRENOBLE ALPES
UNIVERSITAT BASEL
UNIVERSITAT POLITECNICA DE VALENCIA
VOLKSWAGEN AG
ENGINEERING - INGEGNERIA INFORMATICA SPA
Tieto Finland Oy
PHILIPS ELECTRONICS NEDERLAND B.V.
ELECTRICITE DE FRANCE
ABB SCHWEIZ AG
IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE
ZF FRIEDRICHSHAFEN AG
LUXEMBOURG INSTITUTE OF HEALTH
AIRBUS
CENTRAAL BUREAU VOOR DE STATISTIEK
ROBERT BOSCH GMBH

Funding entity:

European Commission
European Commission

Funding call:

H2020-ICT-2018-20
H2020-ICT-2018-20

Funding call URL:

Project #:

952215
952215

Total funding amount:

12.000.000,00€
12.000.000,00€

IIIA funding amount:

135.000,00€
135.000,00€

Duration:

01/Sep/2020
01/Sep/2020
31/Aug/2024
31/Aug/2024

Extension date:

Artificial Intelligence (AI) and all the key digital technologies that are subsumed by the term AI today are an essential part of
the answers to many of the daunting challenges that we are facing. AI will impact the everyday lives of citizens as well as all
business sectors. To maximize the opportunities and minimize the risks, Europe focuses on human-centered Trustworthy AI,
and is taking important steps towards becoming the worldwide centre for Trustworthy AI. Trustworthiness however still
requires significant basic research, and it is clear that the only way to achieve this is through the integration of learning,
optimisation and reasoning, as neither approach will be sufficient on its own.
The purpose of TAILOR is to build a strong academic-public-industrial research network with the capacity of providing the
scientific basis for Trustworthy AI leveraging and combining learning, optimization and reasoning for realizing AI systems
that incorporate the safeguards that make them in the reliable, safe, transparent and respectful of human agency and
expectations. Not only the mechanisms to maximize benefits, but also those for minimizing harm. The network will be based
on a number of innovative state-of-the-art mechanisms. A multi-stakeholder strategic research and innovation research
roadmap coordinates and guides the research in the five basic research programs. Each program forming virtual research
environments with many of the best AI researchers in Europe addressing the major scientific challenges identified in the
roadmap. A collection of mechanisms supporting innovation, commercialization and knowledge transfer to industry. To
support network collaboration TAILOR provides mechanisms such as AI-Powered Collaboration Tools, a PhD program, and
training programs. A connectivity fund to support active dissemination across Europe through for example allowing the
network to grow and to support the scientific stepping up of more research groups.

Artificial Intelligence (AI) and all the key digital technologies that are subsumed by the term AI today are an essential part of
the answers to many of the daunting challenges that we are facing. AI will impact the everyday lives of citizens as well as all
business sectors. To maximize the opportunities and minimize the risks, Europe focuses on human-centered Trustworthy AI,
and is taking important steps towards becoming the worldwide centre for Trustworthy AI. Trustworthiness however still
requires significant basic research, and it is clear that the only way to achieve this is through the integration of learning,
optimisation and reasoning, as neither approach will be sufficient on its own.
The purpose of TAILOR is to build a strong academic-public-industrial research network with the capacity of providing the
scientific basis for Trustworthy AI leveraging and combining learning, optimization and reasoning for realizing AI systems
that incorporate the safeguards that make them in the reliable, safe, transparent and respectful of human agency and
expectations. Not only the mechanisms to maximize benefits, but also those for minimizing harm. The network will be based
on a number of innovative state-of-the-art mechanisms. A multi-stakeholder strategic research and innovation research
roadmap coordinates and guides the research in the five basic research programs. Each program forming virtual research
environments with many of the best AI researchers in Europe addressing the major scientific challenges identified in the
roadmap. A collection of mechanisms supporting innovation, commercialization and knowledge transfer to industry. To
support network collaboration TAILOR provides mechanisms such as AI-Powered Collaboration Tools, a PhD program, and
training programs. A connectivity fund to support active dissemination across Europe through for example allowing the
network to grow and to support the scientific stepping up of more research groups.

2024
Roger Xavier Lera Leri,  Enrico Liscio,  Filippo Bistaffa,  Catholijn M. Jonker,  Maite Lopez-Sanchez,  Pradeep K. Murukannaiah,  Juan A. Rodríguez-Aguilar,  & Francisco Salas-Molina (2024). Aggregating value systems for decision support. Knowledge-Based Systems, 287, 111453. https://doi.org/10.1016/j.knosys.2024.111453. [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]
Marc Serramia,  Manel Rodriguez-Soto,  Maite Lopez-Sanchez,  Juan A. Rodríguez-Aguilar,  Filippo Bistaffa,  Paula Boddington,  Michael Wooldridge,  & Carlos Ansotegui (2023). Encoding Ethics to Compute Value-Aligned Norms. Minds and Machines, 1--30. [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]
Manel Rodríguez Soto,  Maite López-Sánchez,  & Juan A. Rodríguez-Aguilar (2023). Multi-objective reinforcement learning for designing ethical multi-agent environments. Neural Computing and Applications. https://doi.org/10.1007/s00521-023-08898-y. [BibTeX]  [PDF]
Manel Rodríguez Soto,  Roxana Radulescu,  Juan A. Rodríguez-Aguilar,  Maite López-Sánchez,  & Ann Nowé (2023). Multi-objective reinforcement learning for guaranteeing alignment with multiple values. Adaptive and Learning Agents Workshop (AAMAS 2023) . [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]
2022
Nieves Montes,  Nardine Osman,  & Carles Sierra (2022). A computational model of Ostrom's Institutional Analysis and Development framework. Artificial Intelligence, 311, 103756. https://doi.org/10.1016/j.artint.2022.103756. [BibTeX]  [PDF]
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]
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]
Manel Rodríguez Soto,  Juan A. Rodríguez-Aguilar,  & Maite López-Sánchez (2022). Building Multi-Agent Environments with Theoretical Guarantees on the Learning of Ethical Policies. . Adaptive and Learning Agents Workshop at AAMAS 2022 (ALA 2022). [BibTeX]  [PDF]
Nieves Montes,  Nardine Osman,  & Carles Sierra (2022). Combining Theory of~Mind and~Abduction for~Cooperation Under Imperfect Information. Multi-Agent Systems (pp 294--311). Springer International Publishing. https://doi.org/10.1007/978-3-031-20614-6_17. [BibTeX]  [PDF]
Nieves Montes (2022). Engineering Pro-social Values in~Autonomous Agents - Collective and~Individual Perspectives. Multi-Agent Systems (pp 431--434). Springer International Publishing. https://doi.org/10.1007/978-3-031-20614-6_26. [BibTeX]  [PDF]
Nieves Montes (2022). Engineering Socially-Oriented Autonomous Agents and Multiagent Systems. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence . International Joint Conferences on Artificial Intelligence Organization. https://doi.org/10.24963/ijcai.2022/833. [BibTeX]
Manel Rodríguez Soto,  Marc Serramia,  Maite López-Sánchez,  & Juan A. Rodríguez-Aguilar (2022). Instilling moral value alignment by means of multi-objective reinforcement learning. Ethics and Information Technology, 24. https://doi.org/10.1007/s10676-022-09635-0. [BibTeX]  [PDF]
Athina Georgara,  Juan A. Rodríguez-Aguilar,  & Carles Sierra (2022). Privacy-Aware Explanations for Team Formation. Proceedings of the 24th International Conference on Principles and Practice of Multi-Agent Systems . [BibTeX]  [PDF]
Nieves Montes,  & Carles Sierra (2022). Synthesis and Properties of Optimally Value-Aligned Normative Systems. Journal of Artificial Intelligence Research, 74, 1739--1774. https://doi.org/10.1613/jair.1.13487. [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
Nieves Montes,  Nardine Osman,  & Carles Sierra (2021). Enabling Game-Theoretical Analysis of Social Rules. IOS Press. https://doi.org/10.3233/FAIA210120. [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]
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]
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]
Nieves Montes,  & Carles Sierra (2021). Value-Alignment Equilibrium in Multiagent Systems. Fredrik Heintz, Michela Milano, & Barry O'Sullivan (Eds.), Trustworthy AI - Integrating Learning, Optimization and Reasoning (pp 189--204). Springer International Publishing. https://doi.org/10.1007/978-3-030-73959-1_17. [BibTeX]  [PDF]
Nieves Montes,  & Carles Sierra (2021). Value-Guided Synthesis of Parametric Normative Systems. Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (pp. 907–915). International Foundation for Autonomous Agents and Multiagent Systems. [BibTeX]  [PDF]
Lissette Lemus del Cueto
Contract Engineer
Ramon Lopez de Mantaras
Adjunct Professor Ad Honorem
Nardine Osman
Tenured Scientist
Phone Ext. 431826

Juan A. Rodríguez-Aguilar
Research Professor
Phone Ext. 431861

Carles Sierra
Research Professor
Phone Ext. 431801