@InProceedings{selman+1993,
  author       = {Selman, Bart and Kautz, Henry},
  title        = {Domain-independent extensions to {GSAT}},
  booktitle    = {Proceedings of the 13th International Joint Conference on
                  Artifical Intelligence - Volume 1},
  year         = 1993,
  series       = {IJCAI'93},
  pages        = {290–295},
  address      = {San Francisco, CA, USA},
  publisher    = {Morgan Kaufmann Publishers Inc.},
  subtitle     = {Solving large structured satisfiability problems},
  abstract     = {GSAT is a randomized local search procedure for solving
                  propositional satisfiability problems (Selman et
                  al. 1992). GSAT can solve hard, randomly generated problems
                  that are an order of magnitude larger than those that can be
                  handled by more traditional approaches such as the
                  Davis-Putnam procedure. GSAT also efficiently solves
                  encodings of graph coloring problems, N-queens, and Boolean
                  induction. However, GSAT does not perform as well on
                  handcrafted encodings of blocks-world planning problems and
                  formulas with a high degree of asymmetry. We present three
                  strategies that dramatically improve GSAT's performance on
                  such formulas. These strategies, in effect, manage to uncover
                  hidden structure in the formula under considerations, thereby
                  significantly extending the applicability of the GSAT
                  algorithm.},
  numpages     = 6,
  location     = {Chambery, France}
}