Given a hierarchical plan (or schedule) with uncertain task times, we may need to determine the probability that a given plan will satisfy a given deadline. This problem is shown to be NP-hard for series-parallel hierarchies. We provide a polynomial-time approximation algorithm for it. Computing the expected makespan of an hierarchical plan is also shown to be NP-hard. We examine the approximation bounds empirically and demonstrate where our scheme is superior to sampling and to exact computation.

An important problem of automated planning is validating if a plan complies with the domain model. Such validation is straightforward for classical sequential planning but until recently there was no plan validation approach for Hierarchical Task Networks (HTN). In this paper we propose a novel technique for validating HTN plans by parsing of attribute grammars with the timeline constraint.

An important problem of automated planning is validating if a plan complies with the planning domain model. Such validation is straightforward for classical sequential planning but until recently there was no such validation approach for Hierarchical Task Networks (HTN) planning. In this paper we propose a novel technique for validating HTN plans that is based on representing the HTN model as an attribute grammar and using a special parsing algorithm to verify if the plan can be generated by the grammar.

An important problem of automated planning is validating if a plan complies with the planning domain model. Such validation is straightforward for classical sequential planning but until recently there was no such validation approach for Hierarchical Task Networks (HTN) planning. In this paper we propose a novel technique for validating HTN plans that is based on representing the HTN model as an attribute grammar and using a special parsing algorithm to verify if the plan can be generated by the grammar.