2013-2026 Publications

• 2026
  • F. Chouaki, A. Beynier, N. Maudet, P. Viappiani : “Mo-Cem-RL: Multi-Objective Cross-Entropy Method Reinforcement Learning”, The Genetic and Evolutionary Computation Conference, San José, Costa Rica (2026)
  • F. Chouaki, A. Beynier, N. Maudet, P. Viappiani : “Fairness in Cooperative Multi-objective Multi-agent Reinforcement Learning using Expected Utility”, Proceedings of the 25^th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2026), Paphos, Cyprus, pp. 1610–1618, (International Foundation for Autonomous Agents and Multiagent Systems) (2026)
  • F. Chouaki, A. Beynier, N. Maudet, P. Viappiani : “Multi-Objective Categorical Deep Q-Networks”, Proceedings of the 25^th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2026), Paphos, Cyprus, pp. 1610-1618, (International Foundation for Autonomous Agents and Multiagent Systems) (2026)
• 2025
  • F. Chouaki, A. Beynier, N. Maudet, P. Viappiani : “Fairness in Cooperative Multi-agent Multi-objective Reinforcement Learning using the Expected Scalarized Return”, AAMAS '25: Proceedings of the 24^th International Conference on Autonomous Agents and Multiagent Systems, AAMAS '25, Detroit, MI, United States, pp. 2469-2471, (International Foundation for Autonomous Agents and Multiagent Systems), (ISBN: 9798400714269) (2025)
• 2021
  • A. Grivet Sébert, N. Maudet, P. Perny, P. Viappiani : “Preference Aggregation in the Generalised Unavailable Candidate Model”, 7^th International Conference on Algorithmic Decision Theory, vol. 13023, Lecture Notes in Computer Science, Toulouse, France, pp. 35-50, (Springer) (2021)
  • B. Napolitano, O. Cailloux, P. Viappiani : “Simultaneous Elicitation of Scoring Rule and Agent Preferences for Robust Winner Determination”, Proceedings of the 7^th International Conference on Algorithmic Decision Theory (ADT 2021), vol. 13023, Lecture Notes in Computer Science, Toulouse, France, pp. 51-67, (Springer) (2021)
  • C. Manfredotti, P. Viappiani : “A Bayesian Interpretation of the Monty Hall Problem with Epistemic Uncertainty”, The 18^th International Conference on Modeling Decisions for Artificial Intelligence, vol. LNAI, Modeling Decisions for Artificial Intelligence, Umea (Online), Sweden, (Springer) (2021)
  • F. Toffano, P. Viappiani, N. Wilson : “Efficient Exact Computation of Setwise Minimax Regret for Interactive Preference Elicitation”, Proceedings of AAMAS 2021, Online, United Kingdom (2021)
  • A. Grivet Sébert, N. Maudet, P. Perny, P. Viappiani : “Rank Aggregation by Dissatisfaction Minimisation in the Unavailable Candidate Model”, Proceedings of AAMAS 2021, AAMAS '21: Proceedings of the 20^th International Conference on Autonomous Agents and MultiAgent Systems, Online, United Kingdom, pp. 1518-1520, (ACM) (2021)
• 2020
  • O. Nefla, I. Brigui, P. Viappiani, O. Raboun : “Agent-based ordinal classification for group decision making”, The 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT'20), Melbourne (en virtuel), Australia (2020)
  • A. Rico, P. Viappiani : “Incremental Elicitation of Capacities for the Sugeno Integral with a Maximin Approach”, 14^th International Conference on Scalable Uncertainty Management (SUM 2020), Bolzano, Italy (2020)
  • F. Toffano, N. Wilson, P. Viappiani : “Efficient Exact Computation of Setwise Minimax Regret”, The 19^th workshop on Constraint Modelling and Reformulation (ModRef 2020), Louvain-la-Neuve, Belgium (2020)
  • P. Viappiani, C. Boutilier : “On the equivalence of optimal recommendation sets and myopically optimal query sets”, Artificial Intelligence (AIJ), vol. 286, pp. 103328, (Elsevier) (2020)
  • P. Viappiani : “Robust Winner Determination in Positional Scoring Rules with Uncertain Weights”, Theory and Decision, vol. 88 (3), pp. 323–367, (Springer Verlag) (2020)
  • M. Caillat, N. Darcel, C. Manfredotti, P. Viappiani : “Bayesian Vote Elicitation for Group Recommendations”, From Multiple Criteria Decision Aid to Preference Learning (DA2PL 2020), Trento, Italy (2020)
  • O. Nefla, M. Öztürk, P. Viappiani, I. Brigui‑Chtioui, O. Raboun : “Group-based Ordinal Classification based on a Negotiation Process”, Rencontre des Jeunes Chercheur·ses en Intelligence Artificielle, Angers, France, pp. 50-52, (Association française pour l'intelligence artificielle) (2020)
• 2019
  • O. Nefla, M. Öztürk, P. Viappiani, I. Brigui‑Chtioui : “Interactive Elicitation of a Majority Rule Sorting Model with Maximum Margin Optimization”, Algorithmic Decision Theory: 6^th International Conference, ADT 2019, Durham, NC, USA, October 25–27, 2019, Proceedings, Durham, NC, United States (2019)
  • B. Napolitano, O. Cailloux, P. Viappiani : “Simultaneous Elicitation of Committee and Voters’ Preferences”, Rencontres des Jeunes Chercheurs en Intelligence Artificielle 2019, Actes des Rencontres des Jeunes Chercheurs en Intelligence Artificielle 2019, Toulouse, France, pp. 59-62 (2019)
• 2018
  • P. Viappiani : “Positional Scoring Rules with Uncertain Weights”, SUM 2018: Scalable Uncertainty Management, vol. 11142, Lecture Notes in Computer Science, Milan, Italy, pp. 306-320, (Springer) (2018)
• 2017
  • S. Teso, P. Viappiani, A. Passerini : “Constructive Preference Elicitation for Multiple Users with Setwise Maxmargin”, ADT 2017, the 5^th International Conference on Algorithmic Decision Theory, Luxembourg, Luxembourg (2017)
  • H. Gilbert, N. Benabbou, P. Perny, O. Spanjaard, P. Viappiani : “Incremental Decision Making Under Risk with the Weighted Expected Utility Model”, Proceedings of the 26^th International Joint Conference on Artificial Intelligence (IJCAI'17), Melbourne, Australia (2017)
  • N. Benabbou, P. Perny, P. Viappiani : “Incremental elicitation of choquet capacities for multicriteria choice, ranking and sorting problems”, Artificial Intelligence (AIJ), vol. 246, pp. 152-180, (Elsevier) (2017)
• 2016
  • N. Benabbou, P. Perny, P. Viappiani : “A regret-based preference elicitation approach for sorting with multicriteria reference profiles”, From Multicriteria Decision Making to Preference Learning (DA2PL'16), Paderborn, Germany (2016)
  • S. Teso, A. Passerini, P. Viappiani : “Constructive Preference Elicitation by Setwise Max-Margin Learning”, Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16), New York, United States, pp. 2067-2073 (2016)
  • P. Perny, P. Viappiani, A. Boukhatem : “Incremental Preference Elicitation for Decision Making Under Risk with the Rank-Dependent Utility Model”, Uncertainty in Artificial Intelligence, New York, United States (2016)
  • H. Gilbert, B. Zanuttini, P. Viappiani, P. Weng, E. Nicart : “Model-Free Reinforcement Learning with Skew-Symmetric Bilinear Utilities”, Proc. 32^nd Conference on Uncertainty in Artificial Intelligence (UAI~2016), New York City, United States (2016)
  • N. Benabbou, P. Perny, P. Viappiani : “Tri multicritère intéractif basé sur le concept de regret : approches avec seuils de préférences ou profils de référence”, 17^e congrès annuel de la société Française de Recherche Opérationnelle et d’Aide à la Décision (ROADEF 2016), Compiègne, France (2016)
  • N. Benabbou, S. Di Sabatino Di Diodoro, P. Perny, P. Viappiani : “Incremental Preference Elicitation in Multi-Attribute Domains for Choice and Ranking with the Borda Count”, The tenth International Conference on Scalable Uncertainty Management, vol. 9858, Lecture Notes in Computer Science, Nice, France, pp. 81-95, (Springer) (2016)
  • D. Jannach, J. Mengin, B. Mobasher, A. Passerini, P. Viappiani : “Proceedings of the IJCAI 2015 Joint Workshop on Constraints and Preferences for Configuration and Recommendation and Intelligent Techniques for Web Personalization co-located with the 24^th International Joint Conference on Artificial Intelligence (IJCAI 2015)”, IJCAI Joint Workshop on Constraints and Preferences for Configuration and Recommendation and Intelligent Techniques for Web Personalization (CPCR+ITWP 2015) n°1440, Buenos Aires, Argentina, (CEUR Workshop Proceedings) (2016)
  • G. Pigozzi, A. Tsoukiàs, P. Viappiani : “Preferences in Artificial Intelligence”, Annals of Mathematics and Artificial Intelligence, vol. 77 (3-4), pp. 361-401, (Springer Verlag) (2016)
• 2015
  • H. Gilbert, O. Spanjaard, P. Viappiani, P. Weng : “Reducing the Number of Queries in Interactive Value Iteration”, 4^th International Conference on Algorithmic Decision Theory (ADT 2015), vol. 9346, Lecture Notes in Computer Science, Lexington, KY, United States, pp. 139-152, (Springer) (2015)
  • P. Viappiani : “Characterization of Scoring Rules with Distances: Application to the Clustering of Rankings”, Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI 2015), Buenos Aires, Argentina, pp. 104-110 (2015)
  • H. Gilbert, O. Spanjaard, P. Viappiani, P. Weng : “Solving MDPs with Skew Symmetric Bilinear Utility Functions”, 24^th International Joint Conference on Artificial Intelligence (IJCAI-15), Buenos Aires, Argentina, pp. 1989-1995 (2015)
  • N. Benabbou, Ch. Gonzales, P. Perny, P. Viappiani : “Minimax Regret Approaches for Preference Elicitation with Rank-Dependent Aggregators”, EURO Journal on Decision Processes, vol. 3 (1-2), pp. 29-64 (2015)
  • H. Gilbert, O. Spanjaard, P. Viappiani, P. Weng : “Processus décisionnels de Markov avec un tournoi valué sur les politiques”, 16^e congrès annuel de la Société française de recherche opérationnelle et d’aide à la décision (ROADEF), Marseille, France (2015)
• 2014
  • P. Viappiani : “Preference Modeling and Preference Elicitation: An Overview.”, Proceedings of the First International Workshop on Decision Making and Recommender Systems (DMRS2014), vol. 1278, Bolzano, Italy, pp. 19-24, (CEUR Workshop Proceedings) (2014)
  • N. Benabbou, P. Perny, P. Viappiani : “Incremental Elicitation of Choquet Capacities for Multicriteria Decision Making”, Proceedings of the 21^st European Conference on Artificial Intelligence (ECAI'14), vol. 263, Frontiers in Artificial Intelligence and Applications, Prague, Czechia, pp. 87-92 (2014)
  • P. Viappiani : “Aggregation of Uncertain Qualitative Preferences for a Group of Agents”, 15^th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2014, vol. 443, Communications in Computer and Information Science, Montpellier, France, pp. 434-443, (Springer) (2014)
  • M. Zimmer, P. Viappiani, P. Weng : “Teacher-Student Framework: a Reinforcement Learning Approach”, AAMAS Workshop Autonomous Robots and Multirobot Systems, Paris, France (2014)
  • N. Benabbou, P. Perny, P. Viappiani : “Apprentissage des paramètres d’une intégrale de Choquet par regret minimax”, ROADEF - 15^e congrès annuel de la Société française de recherche opérationnelle et d'aide à la décision, Bordeaux, France (2014)
  • P. Viappiani : “Tutoriel : Principled Approaches to Preference Learning”, ROADEF - 15^e congrès annuel de la Société française de recherche opérationnelle et d'aide à la décision, Bordeaux, France (2014)
• 2013
  • A. Tsoukiàs, P. Viappiani : “Tutorial on preference handling”, ACM Conference on Recommender System (RecSys), Hong Kong, China, pp. 497-498 (2013)
  • F. Borzee, V. Mousseau, M. Pirlot, X. Siebert, P. Viappiani : “Bayesian Recommendations and Utility Elicitation with Intensity of Preference Statements”, European Conference on Operational Research, EURO 2013, Preference Learning stream, Rome, Italy (2013)
  • P. Viappiani, P. Perny, Ch. Gonzales : “Elicitation of Non-linear Utility Models”, European Conference on Operations Research, Preference Learning stream, Rome, Italy (2013)
  • M. Jaeger, Th. Nielsen, P. Viappiani : “Twelfth Scandinavian Conference on Artificial Intelligence, SCAI 2013, Aalborg, Denmark, November 20-22, 2013”, Twelfth Scandinavian Conference on Artificial Intelligence, SCAI 2013, vol. 257, Frontiers in Artificial Intelligence and Applications, Aalborg, Denmark, (IOS Press), (ISBN: 978-1-61499-329-2, 978-1-61499-3) (2013)
  • P. Viappiani, Ch. Kroer : “Robust Optimization of Recommendation Sets with the Maximin Utility Criterion”, The 3^rd International Conference on Algorithmic Decision Theory, ADT 2013, vol. 8176, Lecture Notes in Computer Science, Bruxelles, Belgium, pp. 411-424, (Springer Berlin Heidelberg) (2013)
  • P. Viappiani : “Thompson Sampling for Bayesian Bandits with Resets”, Lecture Notes in Computer Science, vol. 8176, Lecture Notes in Computer Science, Bruxelles, Belgium, pp. 399-410, (Springer Berlin Heidelberg) (2013)