  The paper describes a MAS (multi-agent system) simulation approach for
controlling PM10 (Particulate Matter) crisis peaks. A dispersion model is used
with an Artificial Neural Network (ANN) to predict the PM10 concentration
level. The dispersion and ANN models are integrated into a MAS system. PM10
source controllers are modelled as software agents. The MAS is composed of
agents that cooperate with each other for reducing their emissions and control
the air pollution peaks. Different control strategies are simulated and
compared using data from Annaba (North-East Algeria). The simulator helps to
compare and assess the efficiency of policies to control peaks in PM10.
