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» Coarticulation in Markov Decision Processes
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ECAI
1998
Springer
14 years 1 months ago
Optimal Scheduling of Dynamic Progressive Processing
Progressive processing allows a system to satisfy a set of requests under time pressure by limiting the amount of processing allocated to each task based on a predefined hierarchic...
Abdel-Illah Mouaddib, Shlomo Zilberstein
WEBI
2010
Springer
13 years 7 months ago
Impacts of Analysts' Cognitive Styles on the Analytic Process
A user's cognitive style has been found to affect how they search for information, how they analyze the information, and how they make decisions in an analytical process. In ...
Eugene Santos Jr., Hien Nguyen, Fei Yu, Deqing Li,...
ICASSP
2011
IEEE
13 years 24 days ago
Adaptive scalable layer filtering process for video scheduling over wireless networks based on MAC buffer management
In this paper, the problem of scalable video delivery over a timevarying wireless channel is considered. Packet scheduling and buffer management in both Application and Medium Acc...
Nesrine Changuel, Nicholas Mastronarde, Mihaela va...
ATAL
2006
Springer
14 years 24 days ago
Winning back the CUP for distributed POMDPs: planning over continuous belief spaces
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are evolving as a popular approach for modeling multiagent systems, and many different algorithms ha...
Pradeep Varakantham, Ranjit Nair, Milind Tambe, Ma...
IAT
2005
IEEE
14 years 2 months ago
Decomposing Large-Scale POMDP Via Belief State Analysis
Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
Xin Li, William K. Cheung, Jiming Liu