When using a decentralized planning approach in a cooperative multi-agent system, you either can make use of explicit coordination, i.e. using communication and negotiation during the planning phase, or you rely on implicit coordination, i.e. completely decentralized planning with runtime coordination. We will study such an implicit coordination regime in the setting of multi-agent path finding (MAPF).In this setting it is usually assumed that planning is performed centrally and that the destinations of the agents are common knowledge. We will drop both assumptions and analyze under which conditions it can be guaranteed that the agents reach their respective destinations using implicitly coordinated plans without communication. Furthermore, we will analyze what the computational costs associated with such a coordination regime are.
Bernhard Nebel is a Professor at Albert-Ludwigs-Universität Freiburg for the foundations of Artificial Intelligence. He also held positions at the University of Ulm, DFKI, Saarbrücken, IBM Germany, TU Berlin, ISI/USC, and the University of Hamburg. His research interests are automated planning, knowledge representation, and its application in robotics. He is an ACM, AAAI, and EurAI fellow, and he is a member of the German academy of science Lepoldina and a member of Academia Europaea. In 2019, he was named as one of the ten formative minds in German AI history by the German computer science society.
Host: Muhao Chen, POC: Peter Zamar
YOU ONLY NEED TO REGISTER ONCE TO ATTEND THE ENTIRE SERIES – We will send you email announcements with details of the upcoming speakers.
Register in advance for this webinar: https://usc.zoom.us/webinar/register/WN__0VhakI6Q6i3JsasdmNWcA.
After registering, you will receive an email confirmation containing information about joining the Zoom webinar.
The recording for this Interview Seminar talk will be posted on our USC/ISI YouTube page within 1-2 business days: https://www.youtube.com/user/USCISI.