UE Knowledge representation and reasoning

Degrees incorporating this pedagocial element :


The course covers knowledge representation and reasoning algorithms in artificial intelligence. The focus is, in the first part, on logical and symbolic knowledge and, in a second one probabilistic knowledge. The course will cover logical languages, symbolic languages, probabilistic systems, and decision making with these languages and systems.

Outline :

  • Knowledge representation and reasoning based on classical logic: (4 lessons)
    • Rule-based reasoning (forward chaining, backward chaining),
    • Graph-based reasoning (Conceptual graphs, Knowledge graphs)
    • Description logics
  • Uncertain reasoning (4 lessons)
    • Bayesian models
    • Bayesian reasoning
    • Markovian models
  • Spatio-temporal reasoning (2 lessons)
    • Quantitative and qualitative approaches
    • Instant and interval algebra, temporal constraint and reasoning
    • Spatio-temporal reasoning