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ICML
1994
IEEE
14 years 17 days ago
Learning Without State-Estimation in Partially Observable Markovian Decision Processes
Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...
CORR
2008
Springer
154views Education» more  CORR 2008»
13 years 9 months ago
A Counterexample Guided Abstraction-Refinement Framework for Markov Decision Processes
rexample Guided Abstraction-Refinement Framework for Markov Decision Processes ROHIT CHADHA and MAHESH VISWANATHAN Dept. of Computer Science, University of Illinois at Urbana-Champ...
Rohit Chadha, Mahesh Viswanathan
IOR
2008
119views more  IOR 2008»
13 years 9 months ago
Integrating Approximation and Interactive Decision Making in Multicriteria Optimization
We present a new interactive hybrid approach for solving multicriteria optimization problems where features of approximation methods and interactive approaches are incorporated. W...
Kathrin Klamroth, Kaisa Miettinen
ECBS
2008
IEEE
140views Hardware» more  ECBS 2008»
14 years 3 months ago
Towards Performance Related Decision Support for Model Driven Engineering of Enterprise SOA Applications
Model Driven Performance Engineering (MDPE) enables early performance feedback in a MDE process, in order to avoid late identification of performance problems which could cause si...
Mathias Fritzsche, Wasif Gilani, Ivor T. A. Spence...
CAV
2007
Springer
112views Hardware» more  CAV 2007»
14 years 3 months ago
Magnifying-Lens Abstraction for Markov Decision Processes
ng-Lens Abstraction for Markov Decision Processes⋆ In Proc. of CAV 2007: 19th International Conference on Computer-Aided Verification, Lectures Notes in Computer Science. c Spri...
Luca de Alfaro, Pritam Roy