lectures

(Multi-Agent) Reinforcement Learning: a primer, with applications in economics

A self-contained introduction to reinforcement learning (RL) and multi-agent reinforcement learning (MARL) for PhD and Master students in Data Science at Sapienza University of Rome. The course moves from foundational RL concepts and modern deep RL, to the game-theoretic underpinnings of multi-agent systems and core MARL and deep MARL algorithms. In addition to the main theoretical concepts, each lesson includes applications to economic modelling, as well as interactive demos and hands-on coding exercises.




past lectures

2022

  1. AI/ML
    International School for Advanced Studies (SISSA), Workshop
    Lecture and hands-on tutorial on unsupervised learning, May 2022

2021

  1. AI/ML
    University of Trieste, Master course
    Guest lecture on deep learning, Apr 2021
  2. AI/ML for Science
    TU Clausthal, Summer school
    Two day course on machine learning for physics, Mar 2021

2020

  1. AI/ML
    University of Pavia, Summer school
    Mini course on machine learning for physics, Sep 2020

2019

  1. AI/ML for Science
    Aalto University, Workshop
    Lecture on Gaussian process regression for physics, May 2019