A network of cooperating agents must be able to reach rough consensus on a set of topics for cooperation. With highly heterogeneous agents, however, incommensurable measures and i...
Abstract-- We introduce a distributed estimation algorithm for use by a collection of stochastically interacting agents. Each agent has both a discrete value and an estimate of the...
Category ranking is the task of ordering labels with respect to their relevance to an input instance. In this paper we describe and analyze several algorithms for online category r...
Coordinate gradient learning is motivated by the problem of variable selection and determining variable covariation. In this paper we propose a novel unifying framework for coordi...
In this paper, we propose a policy gradient reinforcement learning algorithm to address transition-independent Dec-POMDPs. This approach aims at implicitly exploiting the locality...