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» Approximating Markov Processes by Averaging
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AAAI
2007
15 years 2 months ago
Purely Epistemic Markov Decision Processes
Planning under uncertainty involves two distinct sources of uncertainty: uncertainty about the effects of actions and uncertainty about the current state of the world. The most wi...
Régis Sabbadin, Jérôme Lang, N...
108
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ATAL
2005
Springer
15 years 5 months ago
A polynomial algorithm for decentralized Markov decision processes with temporal constraints
One of the difficulties to adapt MDPs for the control of cooperative multi-agent systems, is the complexity issued from Decentralized MDPs. Moreover, existing approaches can not ...
Aurélie Beynier, Abdel-Illah Mouaddib
UAI
1998
15 years 1 months ago
Hierarchical Solution of Markov Decision Processes using Macro-actions
tigate the use of temporally abstract actions, or macro-actions, in the solution of Markov decision processes. Unlike current models that combine both primitive actions and macro-...
Milos Hauskrecht, Nicolas Meuleau, Leslie Pack Kae...
110
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ECML
2005
Springer
15 years 5 months ago
Using Rewards for Belief State Updates in Partially Observable Markov Decision Processes
Partially Observable Markov Decision Processes (POMDP) provide a standard framework for sequential decision making in stochastic environments. In this setting, an agent takes actio...
Masoumeh T. Izadi, Doina Precup
116
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CORR
2008
Springer
103views Education» more  CORR 2008»
14 years 11 months ago
Quickest Change Detection of a Markov Process Across a Sensor Array
Recent attention in quickest change detection in the multi-sensor setting has been on the case where the densities of the observations change at the same instant at all the sensor...
Vasanthan Raghavan, Venugopal V. Veeravalli