What does "IDEM" mean and what are your main research themes?
Is it more of a basic or applied research topic?
IDEM undertakes fundamental research in applied mathematics at the intersection of information theory and game theory.
The joint use of these theories allows to quantitatively model agents that possesses different amounts of information. Interestingly, the notion of information in the sense of Shannon is rarely taken into account in classical game formulations. Neither are the intricacies of physical channels through which information is sent, e.g., noise, interference, etc. These new considerations parametrize most of the concepts in game theory providing new elements for the analysis of decentralized decision making. These theoretical results have immediate applications in the context of federated learning, particularly on practical policies with which distributed learning machines shall reveal or hide information to their peers in order to improve global metrics, for instance, average generalization errors.
Within this context, the long term objective is to traverse the traditional boundaries between the fields of information theory, data sciences and game theory.
How is the project exploratory?
The exploratory nature of IDEM lies on the fact that it brings together tools from information theory, data sciences, and game theory to study the impact of information on decentralized decision making.
There exist preliminary works involving these theories, but the simultaneous consideration of game and information theories to study decision making models is at this moment a largely uncharted territory.
Do you have academic or industrial partners?
This exploratory action is developed within the existing cooperation of the team NEO with scholars at the University of Sheffield, the National Chiao Tung University in Taiwan and Princeton University.