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» Approximating Markov Processes by Averaging
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AAAI
2007
13 years 9 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...
ATAL
2005
Springer
14 years 29 days 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
13 years 8 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...
ECML
2005
Springer
14 years 28 days 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
CORR
2008
Springer
103views Education» more  CORR 2008»
13 years 7 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