This paper addresses the issue of policy evaluation in Markov Decision Processes, using linear function approximation. It provides a unified view of algorithms such as TD(), LSTD()...
In this paper, we elucidate the equivalence between inference in game theory and machine learning. Our aim in so doing is to establish an equivalent vocabulary between the two dom...
Iead Rezek, David S. Leslie, Steven Reece, Stephen...
Many prominent applications in wireless sensor networks require collected information has to be routed to end nodes in an efficient manner. In general, Connected Dominating Set (C...
The subject of this article is the long standing open problem of developing a general capacity theory for wireless networks, particularly a theory capable of describing the fundam...
Jeffrey G. Andrews, Nihar Jindal, Martin Haenggi, ...
A decision process in which rewards depend on history rather than merely on the current state is called a decision process with non-Markovian rewards (NMRDP). In decisiontheoretic...