UCPOP: a sound, complete, partial order planner for ADL 论文

摘要

We describe the UCPOP partial order planning algorithm which handles a subset of Pednault's ADL action representation. In particular, UCPOP operates with actions that have conditional effects, universally quantified preconditions and effects, and with universally quantified goals. We prove UCPOP is both sound and complete for this representation and describe a practical implementation that succeeds on all of Pednault's and McDermott's examples, including the infamous "Yale Stacking Problem" [McDermott 1991].