Intelligent Systems

Code – 230100   Information and computer science; section: Software of computer equipment and automation systems

Qualification (degree) – Master

Description of course modules (sections, subjects):

  1. Key principles of artificial intelligence, state space representation, decomposable production system.
  2. Different strategies of managing a search in a state space representation (depth-first search, breadth-first search, heuristic search).
  3. Expert systems (architecture, data bases, forward and backward chaining).
  4. Approximate reasoning schemes, expert systems with fuzzy inference.

Syllabus of the course:

State space representation – formalism for representation of artificial intelligence tasks. Production system. Decomposable production system – generalization of the state space representation. AND-OR tree – graphic presentation of the decomposable production system.

Uninformed search management strategies. Depth-first search. Неинформированные Uninformed search management strategies. Breadth-first search. Informed search management strategies. A algorithm. A* algorithm. Heuristics with small and large heuristic force.

Different knowledge presentation models. Forward and backward chaining in production systems. Expert system architecture based on rules. Expert system architecture based on facts. Knowledge bases. Expert system architecture based on facts.

Reasoning in case of uncertain and incomplete information. Approximate reasoning schemes. Multi-stage reasoning. Inference net. Expert system with fuzzy inference.

Teaching methods:

  • lectures,
  • classroom group training directed by a teacher,
  • students’ independent work performed according to the teacher’s task in classrooms and on an extracurricular basis, including use of technical training aids (compulsory),
  • tutorials.

Total hours – 108.

Total credits – 3.

Laboratory work – not applicable.

Form of interim assessment – pass/fail exam.

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