In this paper, we study the problem of learning in the presence of classification noise in the probabilistic learning model of Valiant and its variants. In order to identify the cl...
abstraction of imperfect information games ANDREW GILPIN and TUOMAS SANDHOLM Computer Science Department Carnegie Mellon University Pittsburgh, PA, USA Finding an equilibrium of an...
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...
We introduce a new notion of minors for simplicial complexes (hypergraphs), so-called homological minors. Our motivation is to propose a general approach to attack certain extrema...
We develop a game-theoretic framework for the study of competition between firms who have budgets to “seed” the initial adoption of their products by consumers located in a s...