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AAAI
2000
13 years 9 months ago
Decision Making under Uncertainty: Operations Research Meets AI (Again)
Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
Craig Boutilier
AIPS
2006
13 years 9 months ago
Combining Stochastic Task Models with Reinforcement Learning for Dynamic Scheduling
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...
Malcolm J. A. Strens
TSMC
2008
116views more  TSMC 2008»
13 years 7 months ago
Fuzzy Techniques for Subjective Workload-Score Modeling Under Uncertainties
This paper deals with the development of a computer model to estimate the subjective workload score of individuals by evaluating their heart-rate (HR) signals. The identification o...
Mohit Kumar, D. Arndt, Steffi Kreuzfeld, Kerstin T...
ENTCS
2007
97views more  ENTCS 2007»
13 years 7 months ago
Process Algebra Having Inherent Choice: Revised Semantics for Concurrent Systems
Process algebras are standard formalisms for compositionally describing systems by the dependencies of their observable synchronous communication. In concurrent systems, parallel ...
Harald Fecher, Heiko Schmidt
MP
2006
75views more  MP 2006»
13 years 7 months ago
A Class of stochastic programs with decision dependent uncertainty
We address a class of problems where decisions have to be optimized over a time horizon given that the future is uncertain and that the optimization decisions influence the time o...
Vikas Goel, Ignacio E. Grossmann