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 ...
- Many exciting, emerging applications require that a group of agents share a coherent view of the world given spatial distribution, incomplete and uncertain sensors, and communica...
Robin Glinton, Katia P. Sycara, David Scerri, Paul...
-- Given the overwhelming information appearing in the current web environment, recommendations have been increasingly applied to assist users in handling with the information over...
We present a combinatorial framework for the study of a natural class of distributed optimization problems that involve decisionmaking by a collection of n distributed agents in th...
Using a model of agent behavior based around envy-reducing strategies, we describe an iterated combinatorial auction in which the allocation and prices converge to a solution in t...