Game Theory for Controlling Autonomous Systems

PhD course – Academic year 2025–26

Academic year 2025–26
Instructor Paolo Scarabaggio (paolo.scarabaggio@poliba.it)
Hours of instruction 10 hours
ECTS 1

Goal

This course is designed to provide PhD students with the necessary modeling and methodological tools for analyzing and designing algorithms to solve game equilibrium problems.

Schedule

Date Time
24 June 202610:00 – 12:30
24 June 202613:30 – 16:00
25 June 202610:00 – 12:30
25 June 202613:30 – 16:00

Enrollment

Please use the following link to enroll in the course.


Registration form


In case of problems with the link, please get in touch with the instructor directly at paolo.scarabaggio@poliba.it.

Syllabus

  1. Introduction and motivation
  2. Background
    • Convex Optimization: Convex sets and functions. Set-valued mappings. Normal cone and tangent cone operators. Projection and proximal operators. Lagrangian duality and KKT conditions.
    • Monotone Operator Theory: Fixed points, zeros, and contraction mappings; averaged and nonexpansive mappings; fixed point theorems and algorithms.
  3. Nash equilibrium
    • Nash equilibrium problem and best response mapping.
    • Applications and models: Linear complementarity problems and variational inequalities.
    • Existence and uniqueness of equilibria.
    • Algorithms.
  4. Generalized Nash equilibrium
    • Generalized Nash equilibrium problem.
    • Applications and models: Quasi-variational inequalities and mixed complementarity problems.
    • Existence and uniqueness of equilibria.
    • Algorithms.

Bibliography

Examination method