Schema learning is a way to discover probabilistic, constructivist, predictive action models (schemas) from experience. It includes methods for finding and using hidden state to m...
In designing autonomous agents that deal competently with issues involving time and space, there is a tradeoff to be made between guaranteed response-time reactions on the one han...
— We address the problem of real-time navigation in dynamic environments for car-like robots. Our approach generalizes the concept of velocity obstacles, which have been used for...
Abstract. Probabilistic systems of interacting intelligent agents are considered. They have two sources of uncertainty: uncertainty of communication channels and uncertainty of act...
Michael I. Dekhtyar, Alexander Ja. Dikovsky, Mars ...
Human movements are important cues for recognizing human actions, which can be captured by explicit modeling and tracking of actor or through space-time low-level features. Howeve...