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» Learning by Propagability
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IAT
2007
IEEE
13 years 9 months ago
Resource-Aware Update Policy for Highly Dynamic P2P Networks
As a user attention has become a precious resource, a special care has to be taken to reduce the time needed for answering queries in P2P networks. Existing solutions are usually ...
Dragan Milosevic, Jérôme Kunegis, Sah...
AAAI
1998
13 years 9 months ago
Bayesian Q-Learning
A central problem in learning in complex environmentsis balancing exploration of untested actions against exploitation of actions that are known to be good. The benefit of explora...
Richard Dearden, Nir Friedman, Stuart J. Russell
JMLR
2008
209views more  JMLR 2008»
13 years 7 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
AROBOTS
2004
127views more  AROBOTS 2004»
13 years 7 months ago
Hormone-Inspired Self-Organization and Distributed Control of Robotic Swarms
The control of robot swarming in a distributed manner is a difficult problem because global behaviors must emerge as a result of many local actions. This paper uses a bio-inspired ...
Wei-Min Shen, Peter M. Will, Aram Galstyan, Cheng-...
ICRA
2010
IEEE
150views Robotics» more  ICRA 2010»
13 years 6 months ago
Balancing state-space coverage in planning with dynamics
— Sampling-based kinodynamic planners, such as the popular RRT algorithm, have been proposed as promising solutions to planning for systems with dynamics. Nevertheless, complex s...
Yanbo Li, Kostas E. Bekris