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» Approximating Markov Processes by Averaging
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AIPS
2007
15 years 8 months ago
Discovering Relational Domain Features for Probabilistic Planning
In sequential decision-making problems formulated as Markov decision processes, state-value function approximation using domain features is a critical technique for scaling up the...
Jia-Hong Wu, Robert Givan
AAAI
2010
15 years 7 months ago
Robust Policy Computation in Reward-Uncertain MDPs Using Nondominated Policies
The precise specification of reward functions for Markov decision processes (MDPs) is often extremely difficult, motivating research into both reward elicitation and the robust so...
Kevin Regan, Craig Boutilier
ETT
2002
93views Education» more  ETT 2002»
15 years 5 months ago
Quantum simulation - rare event simulation by means of cloning, thinning and distortion
A method of rare event simulation, termed here quantum simulation, and known also (with some variations) as population Monte Carlo, and Sequential Markov Chain simulation, is appli...
R. G. Addie
SISAP
2009
IEEE
159views Data Mining» more  SISAP 2009»
16 years 26 days ago
Dynamic P2P Indexing and Search Based on Compact Clustering
Abstract—We propose a strategy to perform query processing on P2P similarity search systems based on peers and superpeers. We show that by approximating global but resumed inform...
Mauricio Marín, Veronica Gil Costa, Cecilia...
CSREAESA
2010
15 years 4 months ago
An Approach for Efficient Real Time Moving Object Detection
Moving object detection is essential for real-time surveillance; however, it is challenging to support moving object detection in a timely fashion due to the compute-intensive natu...
Arnab Roy, Sanket Shinde, Kyoung-Don Kang