Aims

Knowledge representation is one of the main topics in
Artificial Intelligence. If we want to write a program that is efficient
in a given context, we need to provide it with a thorough knowledge
of this context. The problem of representation lies mainly in
determining the most adequate formalism for representing knowledge
and the most efficient methods for handling these formalisms.
It is at that very point that a particular representation,
namely the languages of formal logic, comes in.
Most of these languages belong to a class of logic languages called
modal logic.

Main themes

The aim of the course is to present a systematic view of syntax,
semantics and axiomatic systems of modal logic and to show how
different logics used in Artificial Intelligence can be obtained
from particular interpretations of modal logic. The main
logics considered are :

- Deontic logic
- Epistemic logic
- Temporal logic
- Multivalued logics
- Intensional logic
- Modal predicate logic
- Non monotone logic
- Default logic

Other information (prerequisite, evaluation (assessment methods), course materials recommended readings, ...)

Recommended references :

D. Gabbay and F. Guenther,
Hanbook of Philosophical Logic, 4 volumes, D. Reidel.

D. Gabbay, C. Hogger and J. Robinson,
Handbook of Logic in Artificial Intelligence, 5 volumes, Clarendon Press.

A. Thayse,
A Logic Based Approach to Artificial Intelligence, 3 volumes, Wiley.