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ICRA
2007
IEEE
126views Robotics» more  ICRA 2007»
15 years 3 months ago
A formal framework for robot learning and control under model uncertainty
— While the Partially Observable Markov Decision Process (POMDP) provides a formal framework for the problem of robot control under uncertainty, it typically assumes a known and ...
Robin Jaulmes, Joelle Pineau, Doina Precup
IOR
2006
118views more  IOR 2006»
14 years 9 months ago
A Stochastic Programming Approach to Power Portfolio Optimization
The DASH model for Power Portfolio Optimization provides a tool which helps decision-makers coordinate production decisions with opportunities in the wholesale power market. The m...
Suvrajeet Sen, Lihua Yu, Talat Genc
COR
2006
112views more  COR 2006»
14 years 9 months ago
A continuous approach to considering uncertainty in facility design
This paper presents a formulation of the facilities block layout problem which explicitly considers uncertainty in material handling costs on a continuous scale by use of expected...
Bryan A. Norman, Alice E. Smith
FOCS
2004
IEEE
15 years 1 months ago
Stochastic Optimization is (Almost) as easy as Deterministic Optimization
Stochastic optimization problems attempt to model uncertainty in the data by assuming that (part of) the input is specified in terms of a probability distribution. We consider the...
David B. Shmoys, Chaitanya Swamy
AAAI
2006
14 years 11 months ago
Techniques for Generating Optimal, Robust Plans when Temporal Uncertainty is Present
Planning under uncertainty has been well studied, but usually the uncertainty is in action outcomes. This work instead investigates uncertainty in the amount of time that actions ...
Janae N. Foss