Page d'accueil // FSTC // Actualités // Algorithmic decision theory for solving complex decision problems

Algorithmic decision theory for solving complex decision problems

twitter linkedin facebook google+ email this page
Add to calendar
Conférencier : Prof. Dr. Raymond BISDORFF , University of Luxembourg.
Date de l'événement : mercredi, 03 mai 2017, 16:00 - 18:00
Lieu : Campus Belval

About the topic:

Today's decision makers in fields ranging from engineering to psychology, from medicine to economics and/or homeland security are faced with remarkable new technologies, huge amounts of information to help them in reaching good decisions, and the ability to share information at unprecedented speeds and quantities. These tools and resources should lead to better decisions. Yet, the tools bring with them daunting new problems: the massive amounts of data available are often incomplete, unreliable and/or distributed and there is great uncertainty in them; interoperating/distributed decision makers and decision making devices need to be coordinated; many sources of data need to be fused into a good decision; information sharing under new cooperation/competition arrangements raises security problems. When faced with such issues, there are few highly efficient algorithms available to support decision makers.

The objective of Algorithmic Decision Theory (ADT) is to improve the ability of decision makers to perform well when facing these new challenges and problems through the use of methods from theoretical computer science, in particular algorithmic methods. The primary goal of ADT is hence to explore and develop algorithmic approaches for solving decision problems arising in a variety of applications areas. Examples include, but are not limited to:

  •  Computational tractability/intractability of social consensus and multiple criteria compromise functions;
  • Improvement of decision support and recommender systems;
  • Development of automatic decision devices including on-line decision procedures;
  • Robust decision making;
  • Learning for multi-agent systems and other on-line decision devices.

This presentation will focus more specifically on multiple criteria decision aiding methodology, the actual research field of the author.

About the speaker:

Raymond Bisdorff holds an LBA Degree in Business Administration from the University of Liège, Belgium (1975), a MScBA (NATO Graduate Degree Apprenticeship in Systems Sciences grant, 1975-1978) and a PhD in Operations Research (OR), supervisor Prof. B. Roy, from the University Paris-Dauphine (1981). He holds, furthermore, a PhD in Management Sciences from the University of Liège, Belgium (2002). He is since 2003 full professor of Applied Mathematics and Computer Science at the University of Luxembourg, where he teaches courses on algorithmic decision theory, multiple criteria decision aiding, computational statistics and discrete mathematics.

He served the international OR community as president of ORBEL - the Belgian OR society (2008-2010), vice-president of EURO - the Association of European OR Societies (1997-2000) and vice-president of IFORS -the International Federation of OR Societies (2005-2007). He was an honourable collaborator of the Institute of Mathematics at the University of Liège (1996-2005), and of the Polytechnical Faculty of Mons (2010-2017). In 2004, he received an honour diploma from HELLORS -the Hellenic Operational Research Society- for chairing the international Programme Committee of the XXth EURO'2004 Conference, Island of Rhodes. His main research interest is focused on outranking based decision aiding algorithms for selecting, ranking, sorting or rating, and clustering with multiple incommensurable performance criteria of uncertain significance and/or missing data ( see ). His major articles appeared in EJOR, Computers & OR, 4OR and in JMCDA ( see