Dynamic Bayesian Networks to simulate occupant behaviours in office   buildings related to indoor air quality
  This paper proposes a new general approach based on Bayesian networks to model the human behaviour. This approach represents human behaviour with probabilistic cause-effect relations based on knowledge, but also with conditional probabilities coming either from knowledge or deduced from observations. This approach has been applied to the co-simulation of the CO2 concentration in an office coupled with human behaviour. 
Khadija Tijani (CSTB, LIG Laboratoire d'Informatique de Grenoble,   G-SCOP), Stephane Ploix (G-SCOP), Benjamin Haas (CSTB), ...
cs.AI