This paper introduces a multiagent reinforcement learning algorithm that converges with a given accuracy to stationary Nash equilibria in general-sum discounted stochastic games. ...
—Enabling users to connect to the best available network, dynamic network selection scheme is important for satisfying various quality of service (QoS) requirements, achieving se...
Multi-agent games are becoming an increasingly prevalent formalism for the study of electronic commerceand auctions. The speed at which transactions can take place and the growing...
Satinder P. Singh, Michael J. Kearns, Yishay Manso...
Game theory is emerging as a popular tool for distributed control of multiagent systems. In order to take advantage of these game theoretic tools the interactions of the autonomous...
[1, 2] have shown for the dynamic spectrum allocation problem that a competitive market model (which sets a price for transmission power on each channel) leads to a greater social...