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.
