Information and Decision Making (IDEM)

“Information and Decision Making” (IDEM) is an Inria Exploratory Action aiming to contribute in the understanding and modelling of the role of information, e.g., data available, on decision making processes performed by decentralized agents engaged in a given interaction. Interactions between decision makers (DMs), often with different objectives, constraints, and expertise, are traditionally studied under the umbrella of optimization and game theory, for which there exists a large literature. Nonetheless, there are relatively few techniques that formally consider incomplete information, i.e., in the sense of information theory. In a nutshell, in most decision making processes, decisions are made with partial information about the stochastic phenomena underlying the environment in which DMs interact. That is, DMs possess a limited amount of data available and often, this data might have been obtained through systems involving noise; intentional manipulations by external entities; and/or simply impairments due to data transmission or data storage. From this perspective, the data can be useful to inform the DMs and improve their own decision making capabilities; but also, data can be withhold or distorted for steering the behavior of DMs and seek for particular outcomes. This vulnerability to malicious or undesired influence, due to data acquisition and processing, represents a threat for any decentralized decision making process and thus, it must be understood and properly modelled.

Principal Investigators

• Alain Jean-Marie, Inria
• Samir M. Perlaza, Inria

Collaborators

• Prof. Iñaki Esnaola, The University of Sheffield, UK
• Prof. Vincent Poor, Princeton University, NJ, USA
• Prof. Stefano Rini, The National Chao Tung University, Taiwan