On reachability, relevance, and resolution in the planning as satisfiability approach

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


In recent years, there is a growing awareness of the importance of reachability and relevance-based pruning techniques for planning, but little work specifically targets these techniques. In this paper, we compare the ability of two classes of algorithms to propagate and discover reachability and relevance constraints in classical planning problems. The first class of algorithms operates on SAT encoded planning problems obtained using the linear and GRAPHPLAN encoding schemes. It applies unit-propagation and more general resolution steps (involving larger clauses) to these plan encodings. The second class operates at the plan level and contains two families of pruning algorithms: Reachable-k and Relevant-k. Reachable-k provides a coherent description of a number of existing forward pruning techniques used in numerous algorithms, while Relevant-k captures different grades of backward pruning. Our results shed light on the ability of different plan-encoding schemes to propagate information forward and backward and on the relative merit of plan-level and SAT-level pruning methods.

Original languageEnglish
Pages (from-to)1-28
Number of pages28
JournalJournal Of Artificial Intelligence Research
StatePublished - 1 Jan 2001

ASJC Scopus subject areas

  • Artificial Intelligence


Dive into the research topics of 'On reachability, relevance, and resolution in the planning as satisfiability approach'. Together they form a unique fingerprint.

Cite this