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PKDD
2009
Springer
129views Data Mining» more  PKDD 2009»
16 years 1 months ago
Considering Unseen States as Impossible in Factored Reinforcement Learning
Abstract. The Factored Markov Decision Process (FMDP) framework is a standard representation for sequential decision problems under uncertainty where the state is represented as a ...
Olga Kozlova, Olivier Sigaud, Pierre-Henri Wuillem...
VMCAI
2010
Springer
16 years 3 months ago
Best Probabilistic Transformers
This paper investigates relative precision and optimality of analyses for concurrent probabilistic systems. Aiming at the problem at the heart of probabilistic model checking ? com...
Björn Wachter, Lijun Zhang
AAAI
2012
13 years 9 months ago
Tree-Based Solution Methods for Multiagent POMDPs with Delayed Communication
Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
Frans Adriaan Oliehoek, Matthijs T. J. Spaan
QEST
2010
IEEE
15 years 4 months ago
Symblicit Calculation of Long-Run Averages for Concurrent Probabilistic Systems
Abstract--Model checkers for concurrent probabilistic systems have become very popular within the last decade. The study of long-run average behavior has however received only scan...
Ralf Wimmer, Bettina Braitling, Bernd Becker, Erns...
ALDT
2009
Springer
142views Algorithms» more  ALDT 2009»
16 years 1 months ago
Finding Best k Policies
Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...
Peng Dai, Judy Goldsmith