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» A Logic for Modeling Decision Making with Dynamic Preference...
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CCE
2004
13 years 8 months ago
Optimization under uncertainty: state-of-the-art and opportunities
A large number of problems in production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made in the presence of uncer...
Nikolaos V. Sahinidis
AAAI
2008
13 years 11 months ago
Maximum Entropy Inverse Reinforcement Learning
Recent research has shown the benefit of framing problems of imitation learning as solutions to Markov Decision Problems. This approach reduces learning to the problem of recoveri...
Brian Ziebart, Andrew L. Maas, J. Andrew Bagnell, ...
JSAC
2010
107views more  JSAC 2010»
13 years 7 months ago
Online learning in autonomic multi-hop wireless networks for transmitting mission-critical applications
Abstract—In this paper, we study how to optimize the transmission decisions of nodes aimed at supporting mission-critical applications, such as surveillance, security monitoring,...
Hsien-Po Shiang, Mihaela van der Schaar
ATAL
2005
Springer
14 years 2 months ago
Modeling exceptions via commitment protocols
This paper develops a model for exceptions and an approach for incorporating them in commitment protocols among autonomous agents. Modeling and handling exceptions is critical for...
Ashok U. Mallya, Munindar P. Singh
WWW
2009
ACM
14 years 9 months ago
Matchbox: large scale online bayesian recommendations
We present a probabilistic model for generating personalised recommendations of items to users of a web service. The Matchbox system makes use of content information in the form o...
David H. Stern, Ralf Herbrich, Thore Graepel