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PA - C4B - INF581 : Advanced Topics in Artificial Intelligence

Domaine > Informatique.

Descriptif

Driven by recent breakthroughs, rapidly growing collections of data, and a plethora of exciting applications, artificial intelligence is experiencing massive interest and investment from both the academic and industrial scene.

This course selects a number of advanced topics to explore in machine learning and autonomous agents, in particular:

  • Probabilistic graphical models (Bayesian networks, ...)
  • Multi-output and structured-output prediction problems
  • Deep-learning architectures
  • Methods of search and optimization (Beam search, epsilon-approximate search, stochastic optimization, Monte Carlo methods, ...)
  • Sequential prediction and decision making (HMMs, Sequential Monte Carlo, Bayesian Filtering, MDPs, ...)
  • Reinforcement learning (Q-Learning, Deep Q-Learning, ...)

Although these topics are diverse and extensive, this course is developed around a common thread connecting them all, such that each topic builds off the others.

Lectures will cover the relevant theory, and labs will familiarize the students with these topics from a practical point of view. Several of the lab assignments will be graded, and a team project on reinforcement learning will form a major component of the grade - where the goal is to developing and deploy an agent in an environment and write a report analyzing the results.

 

Format des notes

Numérique sur 20

Littérale/grade réduit

Pour les étudiants du diplôme Echanges PEI

Le rattrapage est autorisé (Note de rattrapage conservée)

    Pour les étudiants du diplôme Artificial Intelligence and Advanced Visual Computing

    Le rattrapage est autorisé (Note de rattrapage conservée)

      Pour les étudiants du diplôme Cybersecurity : Threats and Defenses

      Le rattrapage est autorisé (Note de rattrapage conservée)
        L'UE est acquise si note finale transposée >= C
        • Crédits ECTS acquis : 4 ECTS

        Pour les étudiants du diplôme M1 Innovation, Entreprise, et Société - Voie Innovation technologique

        Le rattrapage est autorisé (Note de rattrapage conservée)
          L'UE est acquise si note finale transposée >= C
          • Crédits ECTS acquis : 5 ECTS

          La note obtenue rentre dans le calcul de votre GPA.

          Pour les étudiants du diplôme Diplôme d'ingénieur de l'Ecole polytechnique

          Le rattrapage est autorisé (Note de rattrapage conservée)

            Pour les étudiants du diplôme Cyber Physical System

            Le rattrapage est autorisé
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