Probabilistic Graphical Models and Their Applications in Intelligent Environments

Intelligent environments need to acquire, combine and interpret the user's requests and take the best decisions according to the user needs. Thus, they require intelligent agents that reason under uncertainty to achieve the system goals. Probabilistic graphical models (PGMs) allow intelligent a...

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Bibliographic Details
Published in2012 Eighth International Conference on Intelligent Environments pp. 11 - 15
Main Author Sucar, L. E.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2012
Subjects
Bayesian methods
Games
Graphical models
Markov processes
Probabilistic logic
Temperature sensors
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Summary:Intelligent environments need to acquire, combine and interpret the user's requests and take the best decisions according to the user needs. Thus, they require intelligent agents that reason under uncertainty to achieve the system goals. Probabilistic graphical models (PGMs) allow intelligent agents to reason and take optimal decisions under uncertainty, in an effective and efficient way. We present an overview of PGMs and describe two applications for intelligent environments: (i) information validation, (ii) adaptation to the user.
ISBN:9781467320931
1467320935
DOI:10.1109/IE.2012.66