In this paper, we investigate a family of hill-climbing procedures related to GSAT, a greedy random hill-climbing procedure for satisfiability. These procedures are able to solve large and difficult satisfiability problems beyond the range of conventional procedures like Davis-Putnam. We explore the role of greediness, randomness and hill-climbing in the effectiveness of these procedures. We show that neither greediness nor randomness is crucial to GSAT's performance, and that hill-climbing's importance is limited to a short initial phase of search. In addition, we observe some remarkable and possibly universal features of their search for a satisfying truth assignment. 1 Introduction Many problems in AI are NP-hard and are thus, in general, intractable. A solution to this intractability is to give up completeness; that is, instead of an algorithm which is guaranteed to return an answer, we provide a tractable procedure which will often return an answer but may sometimes term..