The Madagascar planner (M, Mp, MpC) is a very efficient implementation of the SAT based techniques for planning. (MpC and M participated in the "agile" track of the 2014 planning competition and placed respectively 2nd and 3rd, and Madagascar was one of the components of the portfolio planners IBACOP2 and IBACOP that placed respectively 1st and 2nd in the "satisficing" track of the competition.)
J. Rintanen. Heuristic planning with SAT: beyond strict depth-first search. Twenty-Third Australasian Joint Conference on Artificial Intelligence, Adelaide, December 7-10, 2010, Proceedings. Lecture Notes in Computer Science, Springer-Verlag, 2010.
J. Rintanen. Heuristics for planning with SAT. In David Cohen, ed., Principles and Practice of Constraint Programming - CP 2010, 16th International Conference, CP 2010, St. Andrews, Scotland, September 2010, Proceedings. Lecture Notes in Computer Science 6308, pages 414-428, Springer-Verlag, 2010.
J. Rintanen. Planning as satisfiability: heuristics, Artificial Intelligence Journal, 2012.
J. Rintanen. Engineering efficient planners with SAT, In ECAI 2012. Proceedings of the 20th European Conference on Artificial Intelligence, IOS Press, 2012.
J. Rintanen. Planning with specialized SAT solvers. In Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Press, pages 1563-1566, 2011. (© 2011 American Association for Artificial Intelligence. AAAI) (slides)
M. Wehrle and J. Rintanen, Planning as satisfiability with relaxed ∃-step plans, In M. Orgun and J. Thornton, eds, AI 2007 : Advances in Artificial Intelligence: 20th Australian Joint Conference on Artificial Intelligence, Surfers Paradise, Gold Coast, Australia, December 2-6, 2007, Proceedings, Lecture Notes in Computer Science 4830, pages 244-253, Springer-Verlag, 2007. The winner of the AI 2007 Best Paper Award
J. Rintanen, K. Heljanko and I. Niemelä, Planning as satisfiability: parallel plans and algorithms for plan search, Artificial Intelligence, 170(12-13), pages 1031-1080, 2006.
J. Rintanen, Evaluation strategies for planning as satisfiability, in R. Lopez de Mantaras and Lorenza Saitta, eds., ECAI 2004. Proceedings of the 16th European Conference on Artificial Intelligence, pages 682-687, IOS Press, 2004. [additional material on slides of ECAI'04 talk, 4 on 1]