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» Learning for stochastic dynamic programming
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ICML
2009
IEEE
16 years 2 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint
CCE
2008
15 years 2 months ago
Chance constrained programming approach to process optimization under uncertainty
Deterministic optimization approaches have been well developed and widely used in the process industry to accomplish off-line and on-line process optimization. The challenging tas...
Pu Li, Harvey Arellano-Garcia, Günter Wozny
HICSS
2007
IEEE
125views Biometrics» more  HICSS 2007»
15 years 8 months ago
Stochastic Model for Power Grid Dynamics
We introduce a stochastic model that describes the quasistatic dynamics of an electric transmission network under perturbations introduced by random load fluctuations, random rem...
Marian Anghel, Kenneth A. Werley, Adilson E. Motte...
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CISS
2007
IEEE
15 years 5 months ago
Channel-Adaptive Optimal OFDMA Scheduling
Abstract-Joint subcarrier, power and rate allocation in orthogonal frequency division multiple access (OFDMA) scheduling is investigated for both downlink and uplink wireless trans...
Xin Wang, Georgios B. Giannakis, Yingqun Yu
ICTAI
2005
IEEE
15 years 7 months ago
Reachability Analysis for Uncertain SSPs
Stochastic Shortest Path problems (SSPs) can be efficiently dealt with by the Real-Time Dynamic Programming algorithm (RTDP). Yet, RTDP requires that a goal state is always reach...
Olivier Buffet