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» Complex networks as control paradigm for complex systems
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FLAIRS
2007
15 years 10 months ago
Guiding Inference with Policy Search Reinforcement Learning
Symbolic reasoning is a well understood and effective approach to handling reasoning over formally represented knowledge; however, simple symbolic inference systems necessarily sl...
Matthew E. Taylor, Cynthia Matuszek, Pace Reagan S...
IFIP13
2004
15 years 9 months ago
Toward A Human-Centered UML For Risk Analysis
: Safety is now a major concern in many complex systems such as medical robots. A way to control the complexity of such systems is to manage risk. The first and important step of t...
Jérémie Guiochet, Gilles Motet, Clau...
KI
2007
Springer
16 years 1 months ago
Location-Based Activity Recognition
Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract and label a person’s activities and signiļ¬...
Dieter Fox
DATE
2005
IEEE
110views Hardware» more  DATE 2005»
16 years 1 months ago
Test Time Reduction Reusing Multiple Processors in a Network-on-Chip Based Architecture
The increasing complexity and the short life cycles of embedded systems are pushing the current system-onchip designs towards a rapid increasing on the number of programmable proc...
Alexandre M. Amory, Marcelo Lubaszewski, Fernando ...
WDAG
2005
Springer
102views Algorithms» more  WDAG 2005»
16 years 1 months ago
Papillon: Greedy Routing in Rings
We study greedy routing over n nodes placed in a ring, with the distance between two nodes defined to be the clockwise or the absolute distance between them along the ring. Such ...
Ittai Abraham, Dahlia Malkhi, Gurmeet Singh Manku