Inference in Computer Science and in Artificial Intelligence
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Number of hours
Lectures : 18.0
Tutorials : 18.0
ECTS : 2.5
Inference in its different forms (deductive, inductive, probabilistic, abductive,_) pervades almost all the human activities. Different logics systematize inference by using elementary rules schemata, in order to convey information. Applications of automated inference are numerous in Computer Science (particularly in Artificial Intelligence). The main goal of the course is to present a large variety of logics using a unified approach, with special emphasis in expressiveness and logic automation.
Contact Mnacho ECHENIM
Inference, proofs, verification, models. Consequence relation. Non-consequence. Classical logic. Some decidable classes. Subsumption. Generalisation. Equality. Second order logic. Modal logics. Possible worlds semantics. Epistemic logics. Temporal logics. Many-valued and fuzzy logics. Constraint logic programming.