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WIOPT
2011
IEEE
12 years 8 months ago
Open loop optimal control of base station activation for green networks
Abstract—In recent years there has been an increasing awareness that the deployment as well as utilization of new information technology may have some negative ecological impact....
Sreenath Ramanath, Veeraruna Kavitha, Eitan Altman
QUESTA
1998
54views more  QUESTA 1998»
13 years 4 months ago
Optimal control of tandem reentrant queues
We consider optimal policies for reentrant queues in which customers may be served several times at the same station. We show that for tandem reentrant queues the lastbuffer-fir...
Ger Koole, Rhonda Righter
QUESTA
1998
124views more  QUESTA 1998»
13 years 4 months ago
Structural results for the control of queueing systems using event-based dynamic programming
In this paper we study monotonicity results for optimal policies of various queueing and resource sharing models. The standard approach is to propagate, for each specific model, ...
Ger Koole
IJCAI
2003
13 years 6 months ago
Multiple-Goal Reinforcement Learning with Modular Sarsa(0)
We present a new algorithm, GM-Sarsa(0), for finding approximate solutions to multiple-goal reinforcement learning problems that are modeled as composite Markov decision processe...
Nathan Sprague, Dana H. Ballard
ICIP
2003
IEEE
13 years 10 months ago
Stochastic rate-control of interframe video coders for VBR channels
We propose a new algorithm for the real-time control of an interframe video coder operating with a variable rate channel such as wireless channels or the Internet. Using technique...
Julián Cabrera, José Ignacio Ronda, ...
ECAI
2004
Springer
13 years 10 months ago
On-Line Search for Solving Markov Decision Processes via Heuristic Sampling
In the past, Markov Decision Processes (MDPs) have become a standard for solving problems of sequential decision under uncertainty. The usual request in this framework is the compu...
Laurent Péret, Frédérick Garc...
ICML
2002
IEEE
14 years 5 months ago
Hierarchically Optimal Average Reward Reinforcement Learning
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
Mohammad Ghavamzadeh, Sridhar Mahadevan