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PKDD
2010
Springer
164views Data Mining» more  PKDD 2010»
14 years 11 months ago
Efficient Planning in Large POMDPs through Policy Graph Based Factorized Approximations
Partially observable Markov decision processes (POMDPs) are widely used for planning under uncertainty. In many applications, the huge size of the POMDP state space makes straightf...
Joni Pajarinen, Jaakko Peltonen, Ari Hottinen, Mik...
163
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QEST
2010
IEEE
14 years 11 months ago
Reasoning about MDPs as Transformers of Probability Distributions
We consider Markov Decision Processes (MDPs) as transformers on probability distributions, where with respect to a scheduler that resolves nondeterminism, the MDP can be seen as ex...
Vijay Anand Korthikanti, Mahesh Viswanathan, Gul A...
AI
2006
Springer
15 years 5 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...
DMSN
2008
ACM
15 years 3 months ago
Probabilistic processing of interval-valued sensor data
When dealing with sensors with different time resolutions, it is desirable to model a sensor reading as pertaining to a time interval rather than a unit of time. We introduce two ...
Sander Evers, Maarten M. Fokkinga, Peter M. G. Ape...
FSTTCS
2010
Springer
14 years 12 months ago
One-Counter Stochastic Games
We study the computational complexity of basic decision problems for one-counter simple stochastic games (OC-SSGs), under various objectives. OC-SSGs are 2-player turn-based stoch...
Tomás Brázdil, Václav Brozek,...