Composable Markov Building Blocks

  • Authors:

  • Sander Evers;Maarten M. Fokkinga;Peter M. Apers

  • Affiliations:

  • University of Twente, The Netherlands;University of Twente, The Netherlands;University of Twente, The Netherlands

  • Venue:
  • SUM '07 Proceedings of the 1st international conference on Scalable Uncertainty Management
  • Year:
  • 2007

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Abstract

In situations where disjunct parts of the same process are described by their own first-order Markov models and only one model applies at a time (activity in one model coincides with non-activity in the other models), these models can be joined together into one. Under certain conditions, nearly all the information to do this is already present in the component models, and the transition probabilities for the joint model can be derived in a purely analytic fashion. This composability provides a theoretical basis for building scalable and flexible models for sensor data.