Probabilistic Graphical Models and Their Applications in Intelligent Environments

Abstract

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.