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CORR
2012
Springer
235views Education» more  CORR 2012»
13 years 7 months ago
An Incremental Sampling-based Algorithm for Stochastic Optimal Control
Abstract— In this paper, we consider a class of continuoustime, continuous-space stochastic optimal control problems. Building upon recent advances in Markov chain approximation ...
Vu Anh Huynh, Sertac Karaman, Emilio Frazzoli
AAI
2005
117views more  AAI 2005»
14 years 11 months ago
Machine Learning in Hybrid Hierarchical and Partial-Order Planners for Manufacturing Domains
The application of AI planning techniques to manufacturing systems is being widely deployed for all the tasks involved in the process, from product design to production planning an...
Susana Fernández, Ricardo Aler, Daniel Borr...
106
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HRI
2007
ACM
15 years 3 months ago
Efficient model learning for dialog management
Intelligent planning algorithms such as the Partially Observable Markov Decision Process (POMDP) have succeeded in dialog management applications [10, 11, 12] because of their rob...
Finale Doshi, Nicholas Roy
IJCAI
2003
15 years 1 months ago
A Planning Algorithm for Predictive State Representations
We address the problem of optimally controlling stochastic environments that are partially observable. The standard method for tackling such problems is to define and solve a Part...
Masoumeh T. Izadi, Doina Precup
IUI
2010
ACM
15 years 8 months ago
A POMDP approach to P300-based brain-computer interfaces
Most of the previous work on non-invasive brain-computer interfaces (BCIs) has been focused on feature extraction and classification algorithms to achieve high performance for the...
Jaeyoung Park, Kee-Eung Kim, Sungho Jo