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CORR
2010
Springer
105views Education» more  CORR 2010»
15 years 5 months ago
Optimism in Reinforcement Learning Based on Kullback-Leibler Divergence
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Sarah Filippi, Olivier Cappé, Aurelien Gari...
CORR
2010
Springer
205views Education» more  CORR 2010»
15 years 5 months ago
An Algorithm for Detection of Selfish Nodes in Wireless Mesh Networks
—Wireless mesh networks (WMNs) are evolving as a key technology for next-generation wireless networks showing raid progress and numerous applications. These networks have the pot...
Jaydip Sen, Kaustav Goswami
CORR
2008
Springer
151views Education» more  CORR 2008»
15 years 5 months ago
Estimating the Lengths of Memory Words
For a stationary stochastic process {Xn} with values in some set A, a finite word w AK is called a memory word if the conditional probability of X0 given the past is constant on t...
Gusztáv Morvai, Benjamin Weiss
ICRA
2010
IEEE
127views Robotics» more  ICRA 2010»
15 years 5 months ago
Consistent mapping of multistory buildings by introducing global constraints to graph-based SLAM
— In the past, there has been a tremendous advance in the area of simultaneous localization and mapping (SLAM). However, there are relatively few approaches for incorporating pri...
Michael Karg, Kai M. Wurm, Cyrill Stachniss, Klaus...
IJAR
2010
130views more  IJAR 2010»
15 years 5 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki