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ECML
2005
Springer
15 years 9 months ago
Using Rewards for Belief State Updates in Partially Observable Markov Decision Processes
Partially Observable Markov Decision Processes (POMDP) provide a standard framework for sequential decision making in stochastic environments. In this setting, an agent takes actio...
Masoumeh T. Izadi, Doina Precup
PRDC
2006
IEEE
15 years 9 months ago
Detecting and Exploiting Symmetry in Discrete-state Markov Models
Dependable systems are usually designed with multiple instances of components or logical processes, and often possess symmetries that may be exploited in model-based evaluation. T...
W. Douglas Obal II, Michael G. McQuinn, William H....
129
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ACSD
2008
IEEE
106views Hardware» more  ACSD 2008»
15 years 5 months ago
Time-bounded model checking of infinite-state continuous-time Markov chains
The design of complex concurrent systems often involves intricate performance and dependability considerations. Continuous-time Markov chains (CTMCs) are widely used models for co...
Lijun Zhang, Holger Hermanns, Ernst Moritz Hahn, B...
ESANN
2007
15 years 5 months ago
Visualisation of tree-structured data through generative probabilistic modelling
We present a generative probabilistic model for the topographic mapping of tree structured data. The model is formulated as constrained mixture of hidden Markov tree models. A nat...
Nikolaos Gianniotis, Peter Tino
EMNLP
2004
15 years 5 months ago
Comparing and Combining Generative and Posterior Probability Models: Some Advances in Sentence Boundary Detection in Speech
We compare and contrast two different models for detecting sentence-like units in continuous speech. The first approach uses hidden Markov sequence models based on N-grams and max...
Yang Liu, Andreas Stolcke, Elizabeth Shriberg, Mar...