Unité pédagogique

AI Basics - Problem Solving Knowledge Representation and Reasoning

Derniere édition le: 09/12/2024

Modifier

Responsable:

BALBO Flavien

Description générale :

This module is given in English as it corresponds to a teaching units of the M1 International MSc on Cyber Physical and Social Systems (CPS2): AI and IoT

This modules addresses two important fundamental domains of Artificial Intelligence: Problem Solving on one hand and Knowledge Representation and reasoning on the other hand.

For what concerns Problem Solving, the module focuses on automatic decision methods for deciding which actions to carry out when it is necessary to think of several moves in advance, since a single action is not enough to achieve the objective, as in a game of chess. It addresses : 

• Solving Problems by Searching (DFS, BFS, A*, Optimization)
• Adversarial Search (minimax, alpha-beta)
• Constraint Satisfaction Problems (CSP, COP, backtrack , propagation, arc-consistency)

For what concerns Knowledge Representation an Reasoning, the module deals with ways of representing knowledge concerning the environments of intelligent agents and how to reason with this knowledge. It reviews: 

• Logics-based models (propositional, first-order)
• Reasoning schemes (resolution, inference)
• Extensions (fuzzy logics, modal logics)
• Logic Programming (Prolog)
  

Mots-clés:

Modélisation des problèmes Arborescence Graphes Exploration Jeux Recherche de chemin

Nombre d’heures à l’emploi du temps:

36

Domaine(s) ou champs disciplinaires:

Langue d’enseignement:

Anglais

Objectifs d’apprentissage:

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Programme et contenus:

Type d’activité pédagogique :	Contenu, séquencement et organisation
Lectures	(12h)
Supervised work	(12h)
Labs	(16h)