—Reinforcement learning (RL) is a valuable learning method when the systems require a selection of control actions whose consequences emerge over long periods for which input– ...
Previous work has shown that robot navigation systems that employ an architecture based upon the idiotypic network theory of the immune system have an advantage over control techn...
Amanda M. Whitbrook, Uwe Aickelin, Jonathan M. Gar...
Previous work has shown that robot navigation systems that employ an architecture based upon the idiotypic network theory of the immune system have an advantage over control techn...
Amanda M. Whitbrook, Uwe Aickelin, Jonathan M. Gar...
Existing real-time research focuses on how to formulate, model and enforce timeliness guarantees for task sets whose correctness has a temporal aspect. However, the resulting syst...
Claude-Joachim Hamann, Michael Roitzsch, Lars Reut...
We consider the problem of controlling a continuous-time linear stochastic system from a specification given as a Linear Temporal Logic (LTL) formula over a set of linear predicate...
Morteza Lahijanian, Sean B. Andersson, Calin Belta