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  TDDB08 - Logic, advanced course 
 Course language 
English (and logic:)
 Course aim 
The course goal is to provide the participants with a broad knowledge on chosen modern logics and their applications in computer science, in particular in artificial intelligence. Issues on deductive databases as well as incomplete and inaccurate information are also discussed.

The participants will learn how to choose and/or develop a formalism for a particular application domain. Issues of proof systems, with the emphasis on automated verification of satisfiability and validity of formulas, will also be covered.

The course will be given via a sequence of ten lectures. The requirement for satisfactorily completing the course is to demonstrate competence with the course material by solving, in the end of the course, hand-in assignments.
 Course contents 
  • Lecture 1: Modeling and reasoning in logics. Propositional calculus, analytic tableaux.
  • Lecture 2: Automated reasoning with resolution, applications of propositional calculus for expressing concepts and taxonomies, algorithms for checking satisfiability: GSAT, WALKSAT.
  • Lecture 3: Logic and databases, complexity of querying databases using the classical first--order logic, DATALOG.
  • Lecture 4: Automated reasoning with predicate logic: analytic tableaux and resolution.
  • Lecture 5: Reasoning with incomplete information: knowledge representation techniques, commonsense reasoning (circumscription, defaults, defeasible reasoning)
  • Lecture 6: Foundations of Semantic Web technologies: ontologies and description logics.
  • Lecture 7: Reasoning with inconsistent and incomplete information: three- and four-valued logics.
  • Lecture 8: Fuzzy reasoning and its applications in modeling vague concepts and control problems.
  • Lecture 9: Intensional concepts and relations in natural language: modal logics and their applications.
  • Lecture 10: Program verification using dynamic logic.

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Last updated: 2010-03-02