Perception is often seen in multiagent systems and in robotics from a passive point of view. The sensors of the agent collect information on its environment ; however the potentially important number of percepts is not realistic and may decrease the agents efficiency. In this article, we introduce a contextual goal-oriented perception filtering. Besides the lack of plausibility of omniscient agents, it addresses the problem of transmitting too much information to the agents. This goal-oriented perception module is evaluated model in terms of validity of the resulting behavior and of time complexity.
