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» Learning Partially Observable Deterministic Action Models
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ICRA
2010
IEEE
101views Robotics» more  ICRA 2010»
13 years 6 months ago
Searching for objects: Combining multiple cues to object locations using a maximum entropy model
— In this paper, we consider the problem of how background knowledge about usual object arrangements can be utilized by a mobile robot to more efficiently find an object in an ...
Dominik Joho, Wolfram Burgard
CORR
2008
Springer
189views Education» more  CORR 2008»
13 years 7 months ago
Algorithms for Dynamic Spectrum Access with Learning for Cognitive Radio
We study the problem of dynamic spectrum sensing and access in cognitive radio systems as a partially observed Markov decision process (POMDP). A group of cognitive users cooperati...
Jayakrishnan Unnikrishnan, Venugopal V. Veeravalli
AAAI
2011
12 years 7 months ago
Linear Dynamic Programs for Resource Management
Sustainable resource management in many domains presents large continuous stochastic optimization problems, which can often be modeled as Markov decision processes (MDPs). To solv...
Marek Petrik, Shlomo Zilberstein
EDM
2008
97views Data Mining» more  EDM 2008»
13 years 9 months ago
Using Item-type Performance Covariance to Improve the Skill Model of an Existing Tutor
Using data from an existing pre-algebra computer-based tutor, we analyzed the covariance of item-types with the goal of describing a more effective way to assign skill labels to it...
Philip I. Pavlik, Hao Cen, Lili Wu, Kenneth R. Koe...
HRI
2007
ACM
13 years 11 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