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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.
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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.
Prerequisites
Nothing
Personal projects with oral presentations.
N1=P1
N2=P2 si P1<12
Polycopié du cours (contenant problèmes avec solutions) et bibliographie spécifique en rapport avec les projets individuels.
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