Multi Agent Systems (MAS) have recently attracted a lot of interest because of their ability to model many real life scenarios where information and control are distributed among a set of different agents. Practical applications include planning, scheduling, resource allocation, etc.
A major challenge in such systems is coordinating agent actions, such that a globally optimal outcome is achieved. Distributed Constraint OPtimization (DCOP) is a framework that emerged as one of the most successful approaches to coordination in MAS.
This talk will introduce our DPOP algorithm, which largely outperforms all previous DCOP algorithms. I will also discuss dynamic environments (problems can change over time) and a self-stabilizing version of DPOP that can be applied in such settings.
Time permitting, I will also briefly outline some of our recent work in designing truthful mechanisms for systems with self interested agents, and techniques that maintain privacy.
Adrian Petcu obtained his Bachelor's degree in Computer Science from the Polytechnic Institute of Bucharest in 2000. Until 2002, he worked in a software company based in the German part of Switzerland.
In 2002 he started a PhD in the Artificial Intelligence Laboratory of EPFL, in Lausanne, Switzerland. During his PhD he tackled Distributed Constraint Optimization Problems (DCOP) as a means for coordination in Multi Agent Systems (MAS). His main contribution to the field is the introduction of a number of efficient algorithms for DCOP based on dynamic programming. He is also interested in connected issues like mechanism design for systems with self-interested agents, and privacy-preserving algorithms.
Full Curriculum Vitae, list of publications, and other information available at http://liawww.epfl.ch/People/apetcu/