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ICML
2007
IEEE
14 years 11 months ago
Multi-task reinforcement learning: a hierarchical Bayesian approach
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
ATAL
2010
Springer
13 years 11 months ago
Quasi deterministic POMDPs and DecPOMDPs
In this paper, we study a particular subclass of partially observable models, called quasi-deterministic partially observable Markov decision processes (QDET-POMDPs), characterize...
Camille Besse, Brahim Chaib-draa
EC
2006
97views ECommerce» more  EC 2006»
13 years 10 months ago
A Step Forward in Studying the Compact Genetic Algorithm
The compact Genetic Algorithm (cGA) is an Estimation of Distribution Algorithm that generates offspring population according to the estimated probabilistic model of the parent pop...
Reza Rastegar, Arash Hariri
EUROPAR
2006
Springer
14 years 2 months ago
Comparison of Different Methods for Next Location Prediction
Next location prediction anticipates a person's movement based on the history of previous sojourns. It is useful for proactive actions taken to assist the person in an ubiquit...
Jan Petzold, Faruk Bagci, Wolfgang Trumler, Theo U...
VISAPP
2007
13 years 11 months ago
Image deconvolution using a stochastic differential equation approach
We consider the problem of image deconvolution. We foccus on a Bayesian approach which consists of maximizing an energy obtained by a Markov Random Field modeling. MRFs are classi...
Xavier Descombes, M. Lebellego, Elena Zhizhina