Teaching Activities (Enseignements)

Currently, I teach following courses:

Introduction to Reinforcement Learning for Optimal Control

Lecture Slides:
Session 1:
Introduction to Reinforcement Learning,
Markov Decision Process,
Backward recursive Relation
Session 2
Dynamic Programming,
Bellman Equation and Bellman Optimality Equation
Discrete time Linear system control
Session 3
Policy Iteration
Policy Iteration Algorithm
Discrete time Linear Quadratic Regulator
Session 4
Temporal Difference
Function Approximation
Reinforcement Learning for DT Nonlinear system
Session 5
Q-functions, Policy Iteration using Q functions,
Q-learning
Session 6
Policy gradient approaches,
Deep deterministic Policy gradient (DDPG)

Tutorials (TD):
TD1 : Policy Iteration based learning Feedback optimal control law for Linear system in Discrete Time
TD2 : Policy Iteration for unknown Linear Systems using neural networks

TD3 :  Hands on Deep Q-N and DDPG using MATLAB

Deep Reinforcement Learning (DQN and DDPG).

  • Environments solved in Tutorials (OpenAI gym based): Cartpole, Inverted Pendulum and Bipedal Walker

Sûreté de fonctionnement et Retour d'expériences ( Reliability and Feedback Data Collection) ,
4th Year of Engineering in Management opérationnel Maintenance et Maîtrise des risques (M3)

Introduction to Deep Learning and Artificial Intelligence (5th year, Ingénierie de l’Information et des Systèmes (FISE & FISA) :

  • Lectures:
    • Basics  ANN (CM1)
    • CNNs (CM2)
    • RNNs and LSTM (CM3)
  • Practicals (Jupyter notebooks, FISE ONLY):
    •   ANN Basics & classification with MNIST data (TD1, TD2, TD3)
    •  CNN based: (TD4) CIFAR data classification
    • LSTM based:  prediction of time series (TD5)
  • Student Feedback ( in French) 2019-20, 2020-2021 , FISA 2023-24

 

Artificial Intelligence for Prognostics (5th Year, Department M3)

Neural Networks for decision making
CNNs basics and CNNs for Prognostics
RNNs, LSTMs Basics and Deep LSTMs for Prognostics
Course Slides,
Tutorials: TD1, TD2, TD3.

Student Feedback: 2023-2024

Control of Mobile Robots (5A IA2R Parcours SIA)
Lab 1: The QCAR (Autonomous Car),

Lab 2: The QBOT (differential drive robot by Quanser)

Lab3: The 3Pi+ Robot

Lab4: The Zumo robot