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ECML
2005
Springer
15 years 12 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
16 years 11 days 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....
ACSD
2008
IEEE
106views Hardware» more  ACSD 2008»
15 years 8 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 7 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 7 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...