About the workshop

Modern autonomous systems operate in highly interactive environments, where the mutual influence among each other and human operators is non-negligible. Think of self-driving cars in a city environment, drones coordinating deliveries, or robotized warehouses.

Game theory offers a mathematical framework for strategic decision-making in non-cooperative interactions, enabling controllers that  account for the mutual influence of other autonomous systems in the environment, rather than treating each system in isolation. 

This workshop aims at bringing a fresh perspective on the topic by bringing together experts in both foundational theory and applied research, with a strong emphasis on real-world applicability and the practical challenges involved in game-theoretic controller design. The discussion will focus on:

• Computational methods for real-time interactive decision making

• Controller design and autonomous learning in human-robot interactions, autonomous racing, and robot navigation

• Performance guarantees for game-theoretic control

Who this workshop is for

This workshop is intended for anyone interested in leveraging game theory to enable controllers to reason about multi-agent interactions.

Given the interdisciplinary nature of this workshop, we encourage participation from both theory-oriented and application-oriented researchers, in particular from the multi-agent and collaborative robotics community.

We particularly welcome participation from early-career researchers, PhD students and postdocs, as well as professionals from industry.

Speakers

Organizers

• Chinmay Maheshwari - John Hopkins University   

• Giuseppe Belgioioso - KTH Stockholm

• Emilio Benenati - KTH Stockholm - (mail me for questions! 🖂)