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EURONGI
2005
Springer
14 years 3 months ago
An Afterstates Reinforcement Learning Approach to Optimize Admission Control in Mobile Cellular Networks
We deploy a novel Reinforcement Learning optimization technique based on afterstates learning to determine the gain that can be achieved by incorporating movement prediction inform...
José Manuel Giménez-Guzmán, J...
CN
2002
109views more  CN 2002»
13 years 9 months ago
A network infrastructure for IP mobility support in metropolitan areas
The original design of the Internet and its underlying protocols did not anticipate users to be mobile. With the growing interest in supporting mobile users and mobile computing, ...
Cristina Hristea, Fouad A. Tobagi
AROBOTS
2008
158views more  AROBOTS 2008»
13 years 10 months ago
Learning traversability models for autonomous mobile vehicles
Autonomous mobile robots need to adapt their behavior to the terrain over which they drive, and to predict the traversability of the terrain so that they can effectively plan thei...
Michael Shneier, Tommy Chang, Tsai Hong, William P...
ATAL
2004
Springer
14 years 3 months ago
Stigmergic Learning for Self-Organizing Mobile Ad-Hoc Networks (MANET's)
In recent years, mobile ad-hoc networks (MANET’s) have been deployed in various scenarios, but their scalability is severely restricted by the human operators’ ability to conf...
H. Van Dyke Parunak, Sven Brueckner
ATAL
2004
Springer
14 years 3 months ago
Analyzing Stigmergic Learning for Self-Organizing Mobile Ad-Hoc Networks (MANET's)
Abstract. In recent years, mobile ad-hoc networks (MANET’s) have been deployed in various scenarios, but their scalability is severely restricted by the human operators’ abilit...
H. Van Dyke Parunak, Sven Brueckner