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The constraint satisfaction problem (CSP) provides a framework in which it is possible to express, in a natural way,
many
combinatorial problems encountered in artificial intelligence and computer science. In many cases effective
algorithms exist
to solve such a problem, and in others (such as 3SAT) we can show it to be NP-complete. It is conjectured that
every CSP
is either in P or NP-complete, which is the so called dichotomy conjecture. In the course, we will study the
mathematics of
CSP and focus on algebraic methods.
The course may not be taught every academic year.
Last update: Žemlička Jan, doc. Mgr. et Mgr., Ph.D. (14.05.2019)
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Students have to pass exam. The requirements for the exam correspond to what has been done during lectures. Last update: Žemlička Jan, doc. Mgr. et Mgr., Ph.D. (28.10.2019)
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[1] A. Bulatov, A. Krokhin, P. Jeavons: Constraint satisfaction problems and finite algebras. In: Proc. 27th International Colloquium on Automata, Languages and Programming, ICALP'00. Volume 1853 of LNCS, Springer-Verlag (2000) 272-282.
[2] V. Dalmau: Generalized majority-minority operations are tractable. In Proceedings 20th IEEE Symposium on Logic in Computer Science, (LICS 2005),438-447.
[3] T. Feder, M.Y. Vardi: The computational structure of monotone monadic SNP and constraint satisfaction: a study through Datalog and group theory. SIAM J. Computing, 28 (1), 1998, 57-104.
[4] B. Larose, L. Zádori: Bounded width problems and algebras. Algebra Universalis 56 (3-4), 2007, 439-466.
[5] T. J. Schaefer: The complexity of satisfiability problems, in Proc. 10th ACM Symp. on Theory of Computing, ACM, New York, 1978, 216-226.
Last update: T_KA (14.05.2013)
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Solving problems during semester. Last update: Žemlička Jan, doc. Mgr. et Mgr., Ph.D. (28.10.2019)
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1. Definition of CSP, its equivalent forms, basic notions and properties 2. Polymorphisms, algebraic reductions 3. Bounded width problems 4. Schaefer's dichotomy theorem for boolean CSPs 5. Maltsev CSPs
Last update: T_KA (14.05.2013)
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