Memory-bounded techniques have shown great promise in solving complex multi-agent planning problems modeled as DEC-POMDPs. Much of the performance gains can be attributed to pruni...
Markov decisionprocesses(MDPs) haveproven to be popular models for decision-theoretic planning, but standard dynamic programming algorithms for solving MDPs rely on explicit, stat...
We study the problem of estimating the average of a Lipschitz continuous function f defined over a metric space, by querying f at only a single point. More specifically, we explore...
Abstract— Optical Burst and Packet Switching are being considered as the most promising paradigms to increase bandwidth efficiency in IP over DWDM networks. In both cases, due t...
Decentralized Markov decision processes are frequently used to model cooperative multi-agent systems. In this paper, we identify a subclass of general DEC-MDPs that features regul...