Learning algorithms often obtain relatively low average payoffs in repeated general-sum games between other learning agents due to a focus on myopic best-response and one-shot Nas...
In this paper, we describe a new methodology based on game theory for minimizing the average power of a circuit during scheduling in behavioral synthesis. The problem of schedulin...
We consider the problem of learning to predict as well as the best in a group of experts making continuous predictions. We assume the learning algorithm has prior knowledge of the ...
We consider the problem of learning to predict as well as the best in a group of experts making continuous predictions. We assume the learning algorithm has prior knowledge of the ...
We present a novel method for automatically acquiring strategies for the double auction by combining evolutionary optimization together with a principled game-theoretic analysis. ...