Many complex real-world decision problems, such as planning, contain an underlying constraint reasoning problem. The feasibility of a solution candidate then depends on the consis...
Many forms of reasoning about actions and planning can be reduced to regression, the computation of the weakest precondition a state has to satisfy to guarantee the satisfaction of...
In our research we study rational agents which learn how to choose the best conditional, partial plan in any situation. The agent uses an incomplete symbolic inference engine, emp...
This paper provides general information about research at the University of Auckland into autonomous agents in highly dynamic environments, in particular in RoboCup. The paper desc...
This paper describes a reasoning system based on a temporal logic that can solve planning problems along the lines of traditional planning systems. Because it is cast as inference...