Multi Agent Reinforcement Learning
Attention, ce contenu correspond à la fiche de cours de l'année passée
EE-806 / 2 crédits
Enseignant: Cevher Volkan
Langue: Anglais
Remark: 29 to 31 July 2024; Information and Registration via https://sites.google.com/view/marl-school2024/apply?authuser=0
Frequency
Only this year
Summary
The goal of the summer school are providing a rigorous introduction to the foundations of MARL and highlight the challenges that arise in the modern research directions in this area.
Content
- Tutorial 1: Game Theory
- Tutorial 2: Adversarial MDP
- Tutorial 3: Multi Agent RL
- Research Talk 1: Optimistic exploration in Multi Agent RL
- Research Talk 2: Optimization for Multi Agent RL
- Research Talk 3: Applications of Multi Agent RL
- Research Talk 4: Safety in Multi Agent RL
- Research Talk 5: Multi Agent Imitation Learning
Keywords
Reinforcement Learning, Machine Learning, Multi Agent.
Assessment methods
Poster presentation.
Dans les plans d'études
- Nombre de places: 30
- Forme de l'examen: Oral (session libre)
- Matière examinée: Multi Agent Reinforcement Learning
- Cours: 15 Heure(s)
- Type: optionnel