Abstract. Learning to act in an unknown partially observable domain is a difficult variant of the reinforcement learning paradigm. Research in the area has focused on model-free m...
Abstract. We consider the problem of automatically verifying realtime systems with continuously distributed random delays. We generalise probabilistic timed automata introduced in ...
Marta Z. Kwiatkowska, Gethin Norman, Roberto Segal...
Spatio-temporal patterns extracted from historical trajectories of moving objects reveal important knowledge about movement behavior for high quality LBS services. Existing approac...
Abstract--Path openings and closings are morphological operations with flexible line segments as structuring elements. These line segments have the ability to adapt to local image ...
We consider the problem of performing learning and inference in a large scale knowledge base containing imperfect knowledge with incomplete coverage. We show that a soft inference...