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FLAIRS
2004
13 years 8 months ago
Developing Task Specific Sensing Strategies Using Reinforcement Learning
Robots that can adapt and perform multiple tasks promise to be a powerful tool with many applications. In order to achieve such robots, control systems have to be constructed that...
Srividhya Rajendran, Manfred Huber
ADHOC
2004
127views more  ADHOC 2004»
13 years 6 months ago
A distributed and adaptive signal processing approach to exploiting correlation in sensor networks
We propose a novel approach to reducing energy consumption in sensor networks using a distributed adaptive signal processing framework and efficient algorithm 1 . While the topic o...
Jim Chou, Dragan Petrovic, Kannan Ramchandran
IS
2010
13 years 4 months ago
Multicriteria reinforcement learning based on a Russian doll method for network routing
The routing in communication networks is typically a multicriteria decision making (MCDM) problem. However, setting the parameters of most used MCDM methods to fit the preferences ...
Alain Pétrowski, Farouk Aissanou, Ilham Ben...
NIPS
1993
13 years 8 months ago
Packet Routing in Dynamically Changing Networks: A Reinforcement Learning Approach
This paper describes the Q-routing algorithm for packet routing, in which a reinforcement learning module is embedded into each node of a switching network. Only local communicati...
Justin A. Boyan, Michael L. Littman
ATAL
2006
Springer
13 years 10 months ago
Scalable and reliable data delivery in mobile ad hoc sensor networks
This paper studies scalable data delivery algorithms in mobile ad hoc sensor networks with node and link failures. Many algorithms have been developed for data delivery and fusion...
Bin Yu, Paul Scerri, Katia P. Sycara, Yang Xu, Mic...