References
- Aloul, F., Mneimneh, M. and Sakallah, K. (2002). ZBDD-based backtrack search SAT solver,, pp. 131–136.
- Arangú, M. and Salido, M.A. (2011). A fine-grained arc-consistency algorithm for non-normalized constraint satisfaction problems,(4): 733–744, DOI: 10.2478/v10006-011-0058-2.
- Balduccini, M., Gelfond, M. and Nogueira, M. (2006). Answer set based design of knowledge systems,(1–2): 183–219.
- Brewka, G. (1991). Cumulative default logic: In defense of nonmonotonic inference rules,(2): 183–205.
- Davis, M., Logemann, G. and Loveland, D. (1962). A machine program for theorem proving,(7): 394–397.
- Davis, M. and Putnam, H. (1960). A computing procedure for quantification theory,(3): 201–215.
- DIMACS (1993). CNF benchmarks database, ftp://dimacs.rutgers.edu/pub/challenge /sat/benchmarks/cnf/.
- Gelfond, M. and Lifschitz, V. (1988). The stable model semantics for logic programming,R.A. Kowalski and K.A. Bowen (Eds.),, MIT Press, Cambridge, MA, pp. 1070–1080.
- Han, H., Somenzi, F. and Jin, H. (2010). Making deduction more effective in SAT solvers,(8): 1271–1284.
- Hu, Y., Shih, V., Majumdar, R. and He, L. (2008). Exploiting symmetries to speed up SAT-based Boolean matching for logic synthesis of FPGAs,(10): 1751–1760.
- Lukasiewicz, T. and Straccia, U. (2008). Tightly coupled fuzzy description logic programs under the answer set semantics for the semantic web,(3): 68–89.
- Marques-Silva, J. and Sakallah, K. (1999). GRASP: A search algorithm for propositional satisfiability,(5): 506–521.
- Moskewicz, M., Madigan, C., Zhao, Y., Zhang, L. and Malik, S. (2001). Chaff: Engineering an efficient SAT solver,, pp. 530–535.
- Opara, A. and Kania, D. (2010). Decomposition-based logic synthesis for PAL-based CPLDs,(2): 367–384, DOI: 10.2478/v10006-010-0027-1.
- Pułka, A. (2009). Decision supporting system based on fuzzy default reasoning,, pp. 32–39.
- Pułka, A. (2011). An effective SAT-solving mechanism with backtrack controlled by FDL,, pp. 252–257.
- Reiter, R. (1980). A logic for default reasoning,(1): 81–132.
- Suyama, T., Yokoo, M. and Nagoya, A. (1999). Solving satisfiability problems on FPGAs using experimental unit propagation heuristic, parallel and distributed processing,J. Rolim (Ed.),, Lecture Notes in Computer Science, Vol. 1586, Springer-Verlag, Berlin, pp. 709–711.
- Tille, D., Eggersgluss, S. and Drechsler, R. (2010). Incremental solving techniques for SAT-based ATPG,(7): 1125–1130.
- Wyrwoł, B. and Hrynkiewicz, E. (2013). Decomposition of the fuzzy inference system for implementation in the FPGA structure,(2): 473–483, DOI: 10.2478/amcs-2013-0036.
- Yin, L., He, F., Hung, W., Song, X. and Gu, M. (2012). Maxterm covering for satisfiability,(3): 420–426.
- Zadeh, L.A. (2006). Generalized theory of uncertainty (GTU)—principal concepts and ideas,(1): 15–46.
- Zadeh, L.A. (2008). Is there a need for fuzzy logic?,(13): 2751–2779.
Language: English
Page range: 283 - 297
Submitted on: Jan 13, 2013
Published on: Jun 26, 2014
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
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© 2014 Andrzej Pułka, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.