er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
The dominant existing routing strategies employed in peerto-peer(P2P) based information retrieval(IR) systems are similarity-based approaches. In these approaches, agents depend o...
Abstract—In this paper, we study how to optimize the transmission decisions of nodes aimed at supporting mission-critical applications, such as surveillance, security monitoring,...
Recent research has shown the benefit of framing problems of imitation learning as solutions to Markov Decision Problems. This approach reduces learning to the problem of recoveri...
Brian Ziebart, Andrew L. Maas, J. Andrew Bagnell, ...
In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...