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» Mean-Variance Optimization in Markov Decision Processes
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AAAI
1996
14 years 11 months ago
Computing Optimal Policies for Partially Observable Decision Processes Using Compact Representations
: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...
Craig Boutilier, David Poole
AUSAI
2008
Springer
14 years 11 months ago
An Optimality Principle for Concurrent Systems
Abstract. This paper presents a formulation of an optimality principle for a new class of concurrent decision systems formed by products of deterministic Markov decision processes ...
Langford B. White, Sarah L. Hickmott
AI
2006
Springer
15 years 1 months ago
Trace Equivalence Characterization Through Reinforcement Learning
In the context of probabilistic verification, we provide a new notion of trace-equivalence divergence between pairs of Labelled Markov processes. This divergence corresponds to the...
Josee Desharnais, François Laviolette, Kris...
ORL
2006
87views more  ORL 2006»
14 years 9 months ago
SPAR: stochastic programming with adversarial recourse
We consider a general adversarial stochastic optimization model. Our model involves the design of a system that an adversary may subsequently attempt to destroy or degrade. We int...
Matthew D. Bailey, Steven M. Shechter, Andrew J. S...
SOCIALCOM
2010
14 years 7 months ago
A Decision Theoretic Approach to Data Leakage Prevention
Abstract--In both the commercial and defense sectors a compelling need is emerging for rapid, yet secure, dissemination of information. In this paper we address the threat of infor...
Janusz Marecki, Mudhakar Srivatsa, Pradeep Varakan...