We consider the problem of learning to attain multiple goals in a dynamic environment, which is initially unknown. In addition, the environment may contain arbitrarily varying ele...
We dene the probabilistic planning problem in terms of a probability distribution over initial world states, a boolean combination of goal propositions, a probability threshold, ...
We describe a robot control architecture which combines a stimulus-response subsystem for rapid reaction, with a search-based planner for handling unanticipated situations. The ro...
Abstract. We apply model checking of knowledge properties to the design of distributed controllers that enforce global constraints on concurrent systems. We calculate when processe...
Industry is looking to create a market in reliable "plug-and-play" components. To model components in a modular style it would be useful to combine event-based and state...