Learning, planning, and representing knowledge in large state t multiple levels of temporal abstraction are key, long-standing challenges for building flexible autonomous agents. ...
Temporal planning (TP) is notoriously difficult because it requires to solve a propositional STRIPS planning problem with temporal constraints. In this paper, we propose an efficie...
Many perceptual processes and neural computations, such as speech recognition, motor control and learning, depend on the ability to measure and mark the passage of time. However, ...
This paper concerns recognition of human actions under view changes. We explore self-similarities of action sequences over time and observe the striking stability of such measures ...
Imran N. Junejo, Emilie Dexter, Ivan Laptev, Patri...
— In this work, we perform an extensive statistical evaluation for learning and recognition of object manipulation actions. We concentrate on single arm/hand actions but study th...