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IJCAI
2001
15 years 2 months ago
Complexity of Probabilistic Planning under Average Rewards
A general and expressive model of sequential decision making under uncertainty is provided by the Markov decision processes (MDPs) framework. Complex applications with very large ...
Jussi Rintanen
MOR
2008
87views more  MOR 2008»
15 years 23 days ago
On Near Optimality of the Set of Finite-State Controllers for Average Cost POMDP
We consider the average cost problem for partially observable Markov decision processes (POMDP) with finite state, observation, and control spaces. We prove that there exists an -...
Huizhen Yu, Dimitri P. Bertsekas
126
Voted
SOCO
2010
Springer
14 years 7 months ago
Using evolution strategies to solve DEC-POMDP problems
Decentralized partially observable Markov decision process (DEC-POMDP) is an approach to model multi-robot decision making problems under uncertainty. Since it is NEXP-complete the...
Baris Eker, H. Levent Akin
ECOOPW
2003
Springer
15 years 6 months ago
Modeling Variability for Object-Oriented Product Lines
The concept of a software product line is a promising approach for increasing planned reusability in industry. For planning future requirements, the integration of domain analysis ...
Matthias Riebisch, Detlef Streitferdt, Ilian Pasho...
89
Voted
DATE
2007
IEEE
92views Hardware» more  DATE 2007»
15 years 7 months ago
Dynamic power management under uncertain information
This paper tackles the problem of dynamic power management (DPM) in nanoscale CMOS design technologies that are typically affected by increasing levels of process, voltage, and te...
Hwisung Jung, Massoud Pedram