Team : DECISION - Translate hereAxes : AID (👥👥), TMC (👥👥).
Team leader :
Patrice Perny Campus Pierre et Marie Curie 26-00/411
The Decision team works on the development of formal models and algorithms for decision-making and for optimization in complex environments (uncertainty and risk, multicriteria decision-making, collective decision-making, context) as well as the development of decision-aiding systems. Our research deals with on the one hand the elaboration or the analysis of sophisticated models to take into account complex decision behaviors and on the other hand the conception of optimization algorithms allowing the preferred solutions to be determined on discrete or continuous domains. The potential applications are decision-aiding systems (rational preparation of important decisions, recommending systems on the web), automatic decision-making (autonomous decision agents) and optimization in large systems (telecommunication, transport, energy). The main research themes of the Decision team: – preference and belief modeling under uncertainty and risk – multicriteria aggregation, preference aggregation for collective decision-making – heuristic search in state graphs for decision-making – stochastic optimization and robust optimization models – decomposition methods for optimization in large systems – algebraic models for decision-aiding – graphical models for reasoning and decision-making (Bayesian nets and GAI nets) – context-based decision-making and explanation Positioning: 1. The competences of the team cover the whole range of decision problems from the development of theoretical models and their mathematical justification, to real applications, through problem modeling and the development of algorithms and decision systems. 2. Our works, due to the formal tools they use and combine but also due to the addressed problems, deal with Operations research as well Artificial Intelligence and the team publishes in both communities. (the webpages from this link are under the responsibility of the head of the team)
Decision-making under uncertainty and risk, multicriteria decision-making, group decision-making, preference modeling, optimization, graphs and algorithms, heuristic search, Bayesian nets, GAI nets.
No event planned at present.Archives
- M. Herin, P. Perny, N. Sokolovska : “Learning Preference Models with Sparse Interactions of Criteria”IJCAI 2023 - The 32nd International Joint Conference On Artificial Intelligence, Macao, China[Herin 2023b]
- H. Ouzia, R. Vicente Pinto, N. Maculan : “A New Second-Order Conic Optimization Model for the Euclidean Steiner Tree Problem in R^d”International Transactions in Operational Research, (Wiley)[Ouzia 2023]
- B. Escoffier, O. Spanjaard, M. Tydrichová : “Weighted majority tournaments and Kemeny ranking with 2-dimensional Euclidean preferences”Discrete Applied Mathematics, vol. 318, pp. 6-12, (Elsevier)[Escoffier 2022b]
- M. Herin, P. Perny, N. Sokolovska : “Learning Sparse Representations of Preferences within Choquet Expected Utility Theory”Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, vol. 180, Proceedings of Machine Learning Research, Eindhoven, Netherlands, pp. 800-810, (PMLR)[Herin 2022b]
- N. Gross‑Humbert, N. Benabbou, A. Beynier, N. Maudet : “Sequential and Swap Mechanisms for Public Housing Allocation with Quotas and Neighbourhood-Based Utilities (Extended Abstract)”Proceedings of the 20th International Conference on Autonomous Agentsand Multiagent Systems (AAMAS 2021), London / Online, United Kingdom[Gross-Humbert 2021]
- N. Benabbou, C. Leroy, Th. Lust, P. Perny : “Combining Preference Elicitation with Local Search and Greedy Search for Matroid Optimization”Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI'21), Virtual, France[Benabbou 2021a]
- M. Lasserre, R. Lebrun, P.‑H. Wuillemin : “Constraint-based learning for non-parametric continuous bayesian networks”Annals of Mathematics and Artificial Intelligence, vol. 89, pp. 1035-1052, (Springer Verlag)[Lasserre 2021b]
- N. Benabbou, H. Martin, P. Perny : “Min Cost Improvement and Max Gain Stability in Multicriteria Sorting Methods on Combinatorial Domains”Journal of Multi-Criteria Decision Analysis, (Wiley)[Benabbou 2021d]
- V. Nguyen, M. Minoux : “Linear size MIP formulation of Max-Cut: new properties, links with cycle inequalities and computational results”Optimization Letters, (Springer Verlag)[Nguyen 2020]
- P. Brézillon : “Modeling and Using Context: 25 Years of Lessons Learned” chapter in Modeling and Use of Context in Action, (Wiley & Sons Ltd), (ISBN: 978-1-78630-829-0)[Brézillon 2022a]