1. Audemard, G., Simon, L.: Predicting learnt clauses quality in modern SAT solvers. In: Boutilier, C. (ed.) IJCAI 2009, Proceedings of the 21st International Joint Conference on Artificial Intelligence, Pasadena, California, USA, 11–17 July 2009, pp. 399–404 (2009).
http://ijcai.org/Proceedings/09/Papers/074.pdf
2. Beame, P., Kautz, H.A., Sabharwal, A.: Towards understanding and harnessing the potential of clause learning. J. Artif. Intell. Res. 22, 319–351 (2004).
https://doi.org/10.1613/jair.1410
3. Biere, A.: CADICAL at the SAT race 2019. In: Heule, M.J.H., Järvisalo, M., Suda, M. (eds.) Proceedings of SAT Competition 2019 Solver and Benchmark Descriptions. University of Helsinki (2019).
http://hdl.handle.net/10138/306988
4. Biere, A.: Cadical SAT solver (2019).
https://github.com/arminbiere/cadical
5. Bayardo Jr, R.J., Schrag, R.: Using CSP look-back techniques to solve real-world SAT instances. In: Kuipers, B., Webber, B.L. (eds.) Proceedings of the Fourteenth National Conference on Artificial Intelligence and Ninth Innovative Applications of Artificial Intelligence Conference, AAAI 97, IAAI 97, 27–31 July 1997, Providence, Rhode Island, USA, pp. 203–208. AAAI Press/The MIT Press (1997).
http://www.aaai.org/Library/AAAI/1997/aaai97-032.php