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

An introduction to reinforcement learning (RL) and multi-agent reinforcement learning (MARL) with applications in economics. The course covers foundational RL concepts (L1), modern deep RL approaches (L2), game-theoretic foundations of multi-agent systems (L3) and basic MARL and deep MARL algorithms (L4), with interactive demonstrations and hands-on coding exercises.

Course by Aldo Glielmo.

Lesson 1: Introduction & RL Basics

📄 Presentation slides 📄 L1 slides 🎮 Demo: dynamic programming 🎮 Demo: tabular RL 💻 Code for hands-on session

Lesson 2: Deep RL

📄 L2 slides 🎮 Demo: DQN with SB3 📄 Application in economics: Natural-gas storage modelling 💻 Code for hands-on session

Lesson 3: Games and MARL Basics

📄 L3 slides 🎮 Demo: matrix games 🎮 Demo: solution concepts 📄 Application in economics: Robust policy design (G. Bertone & A. Meligrana) 💻 Code for hands-on session