We use game theory to analyze meta-learning algorithms. The objective of meta-learning is to determine which algorithm to apply on a given task. This is an instance of a more gene...
Abstract--This paper considers the noncooperative maximization of mutual information in the vector Gaussian interference channel in a fully distributed fashion via game theory. Thi...
Certain observable features (tags), shared by a group of similar agents, can be used to signal intentions and can be effectively used to infer unobservable properties. Such infere...
Abstract— Standard embeded sensor nework models emphasize energy efficiency and distributed decision-making by considering untethered and unattended sensors. To this we add two ...
Rajgopal Kannan, Sudipta Sarangi, S. Sitharama Iye...
While there is a broad theoretic foundation for creating computational players for two-player games, such as Chess, the multi-player domain is not as well explored. We make an att...