Learning in real-world domains often requires to deal with continuous state and action spaces. Although many solutions have been proposed to apply Reinforcement Learning algorithm...
Alessandro Lazaric, Marcello Restelli, Andrea Bona...
Abstract— To compute collision-free and dynamicallyfeasibile trajectories that satisfy high-level specifications given in a planning-domain definition language, this paper prop...
An extension to action systems is presented facilitating the modeling of continuous behavior in the discrete domain. The original action system formalism has been developed by Back...
Bernhard K. Aichernig, Harald Brandl, Willibald Kr...
We define the robustness of a sequential plan as the probability that it will execute successfully despite uncertainty in the execution environment. We consider a rich notion of u...
Many human action recognition tasks involve data that can be factorized into multiple views such as body postures and hand shapes. These views often interact with each other over ...