Paper Info
Title
Minimal Disclosure in Partially Observable Markov Decision Processes.
Abstract
For security and efficiency reasons, most systems do not give the users a full access to their information. One key specification formalism for these systems are the so called Partially Observable Markov Decision Processes (POMDP for short), which have been extensively studied in several research communities, among which AI and model-checking. In this paper we tackle the problem of the minimal information a user needs at runtime to achieve a simple goal, modeled as reaching an objective with probability one. More precisely, to achieve her goal, the user can at each step either choose to use the partial information, or pay a fixed cost and receive the full information. The natural question is then to minimize the cost the user needs to fulfill her objective. This optimization question gives rise to two different problems, whether we consider to minimize the worst case cost, or the average cost. On the one hand, concerning the worst case cost, we show that efficient techniques from the model checking community can be adapted to compute the optimal worst case cost and give optimal strategies for the users. On the other hand, we show that the optimal average price (a question typically considered in the AI community) cannot be computed in general, nor can it be approximated in polynomial time even up to a large approximation factor.
Year
DOI
Venue
2011
10.4230/LIPIcs.FSTTCS.2011.411
Leibniz International Proceedings in Informatics
Keywords
Field
DocType
Partially Observable Markov Decision Processes,Stochastic Games,Model-Checking,Worst-Case/Average-Case Analysis
Combinatorics,Mathematical optimization,Model checking,Observable,Computer science,Partially observable Markov decision process,Markov decision process,Fixed cost,Average cost,Formalism (philosophy),Time complexity
Conference
Volume
ISSN
Citations 
13
1868-8969
0
PageRank 
References 
Authors
0.34
15
2
Name
Order
Citations
PageRank
Nathalie Bertrand125017.84
Blaise Genest230425.09