We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
— We study large population stochastic dynamic games where each agent receives influences from multi-classes of agents according to intra- and inter-subpopulation cost coupling....
—In this paper, recent results in game theory and stochastic approximation are brought together to mitigate the problem of femto-to-macrocell cross-tier interference. The main re...
We reexamine what it means to compute Nash equilibria and, more generally, what it means to compute a fixed point of a given Brouwer function, and we investigate the complexity o...
This paper proposes the β-WoLF algorithm for multiagent reinforcement learning (MARL) in the stochastic games framework that uses an additional “advice” signal to inform agen...