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AAAI
1994
15 years 1 months ago
Acting Optimally in Partially Observable Stochastic Domains
In this paper, we describe the partially observable Markov decision process pomdp approach to nding optimal or near-optimal control strategies for partially observable stochastic ...
Anthony R. Cassandra, Leslie Pack Kaelbling, Micha...
ICIP
2003
IEEE
16 years 1 months ago
Object localization using texture motifs and Markov random fields
This work presents a novel approach to object localization in complex imagery. In particular, the spatial extents of objects characterized by distinct spatial signatures at multip...
Shawn Newsam, Sitaram Bhagavathy, B. S. Manjunath
PERCOM
2007
ACM
15 years 11 months ago
Sensor Scheduling for Optimal Observability Using Estimation Entropy
We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process ...
Mohammad Rezaeian
ML
2002
ACM
146views Machine Learning» more  ML 2002»
14 years 11 months ago
Variable Resolution Discretization in Optimal Control
Abstract. The problemof state abstractionis of centralimportancein optimalcontrol,reinforcement learning and Markov decision processes. This paper studies the case of variable reso...
Rémi Munos, Andrew W. Moore
CDC
2009
IEEE
134views Control Systems» more  CDC 2009»
15 years 4 months ago
Event-based control using quadratic approximate value functions
Abstract— In this paper we consider several problems involving control with limited actuation and sampling rates. Event-based control has emerged as an attractive approach for ad...
Randy Cogill