This paper describes an extension of graphplan to a subset of ADL that allows conditional and universally quanti ed e ects in operators. The data structure of planning graphs is extended to cope with the more expressive operators in such a way that all interesting properties of the original graphplan formalism are preserved. We present a sound and complete planning algorithm that extracts plans from planning graphs and that terminates on unsolvable problems. Results from an empirical evaluation demonstrate that this extension of the original graphplan system comes with almost no computational overhead if carefully implemented. The resulting system is the kernel algorithm of our own interference progression planner IP 2 that competes very well with other complete planners for operators with conditional and universally quanti ed e ects such as UCPOP and Prodigy.
This is the case in several extensions of the Graphplan algorithm that handle conditional effects REF , and incomplete initial states .
Extending Planning Graphs to an ADL Subset
ECP
Computer Science