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ECML
2005
Springer
14 years 3 months ago
Active Learning in Partially Observable Markov Decision Processes
This paper examines the problem of finding an optimal policy for a Partially Observable Markov Decision Process (POMDP) when the model is not known or is only poorly specified. W...
Robin Jaulmes, Joelle Pineau, Doina Precup
ICN
2005
Springer
14 years 3 months ago
Maximizing System Value Among Interested Packets While Satisfying Time and Energy Constraints
: Data filtering is an important approach to reduce energy consumption. Following this idea, Interest is used as a constraint to filter uninterested data in sensor networks. Within...
Lei Shu, Sungyoung Lee, Xiaoling Wu, Jie Yang
INFOCOM
2002
IEEE
14 years 3 months ago
Optimal Energy Allocation and Admission Control for Communications Satellites
—We address the issue of optimal energy allocation and admission control for communications satellites in earth orbit. Such satellites receive requests for transmission as they o...
Alvin Fu, Eytan Modiano, John N. Tsitsiklis
ROBOCUP
2001
Springer
75views Robotics» more  ROBOCUP 2001»
14 years 2 months ago
A Modular Hierarchical Behavior-Based Architecture
Abstract. This paper describes a highly modular hierarchical behaviorbased control system for robots. Key features of the architecture include: easy addition/removal of behaviors, ...
Scott Lenser, James Bruce, Manuela M. Veloso
WSC
2008
14 years 12 days ago
On step sizes, stochastic shortest paths, and survival probabilities in Reinforcement Learning
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
Abhijit Gosavi