Learning to converge to an efficient, i.e., Pareto-optimal Nash equilibrium of the repeated game is an open problem in multiagent learning. Our goal is to facilitate the learning ...
In this paper, we consider the development of single-timescale schemes for the distributed computation of Nash equilibria. In general, equilibria associated with convex Nash games ...
Agents engaged in noncooperative interaction may seek to achieve a Nash equilibrium; this requires that agents be aware of others’ rewards. Misinformation about rewards leads to...
Cut games and party affiliation games are well-known classes of potential games. Schaffer and Yannakakis showed that computing pure Nash equilibrium in these games is PLScomplete....
Consider a network vulnerable to viral infection. The system security software can guarantee safety only to a limited part of the network. Such limitations result from economy cos...
Marios Mavronicolas, Vicky G. Papadopoulou, Anna P...