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PKDD
2009
Springer
129views Data Mining» more  PKDD 2009»
15 years 8 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
15 years 11 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 4 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
14 years 11 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»
15 years 8 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