Algorithms for deriving summary information about propositional and metric resource conditions and effects, and for using such information to determine potential and definite interactions between abstract tasks.

We prove that our summarization techniques are guaranteed to correctly capture all of the conditions and effects associated with an abstract operator appropriately, augmented with modal information about whether conditions must or may hold and whether they hold during the entire operation or only for some of the time. Because summary information captures all conditions and effects, our algorithms can reason with operators at different levels of abstraction to predict and often resolve operator interactions without fully detailing task hierarchies, even for operators that are executing asynchronously at different agents.