We consider the equivalence problem for labeled Markov chains (LMCs), where each state is labeled with an observation. Two LMCs are equivalent if every finite sequence of observat...
Laurent Doyen, Thomas A. Henzinger, Jean-Fran&cced...
"From an applications viewpoint, the main reason to study the subject of these notes is to help deal with the complexity of describing random, time-varying functions. A random...
Traditionally, Markov models have not been successfully used for compression of signal data other than binary image data. Due to the fact that exact substring matches in non-binar...
Markov Random Fields are widely used in many image processing applications. Recently the shortcomings of some of the simpler forms of these models have become apparent, and models ...
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function....