Mar 6, 2017
Jolley Hall, Room 309
Distributed Constraint Optimization: Model, Algorithms, and Applications
Department of Computer Science
New Mexico State University
A Distributed Constraint Optimization Problem (DCOP) is a problem where several agents coordinate with each other to take on values so as to minimize the sum of the resulting constraint costs, which are dependent on the values of the agents. DCOPs are rapidly becoming popular for formulating and solving multi-agent coordination problems such as the distributed coordination of sensors in a network and the distributed scheduling of meetings.
In this talk, I will first describe the formulation for a DCOP and the motivation for using DCOPs in multi-agent coordination problems. I will then provide a brief overview on the leading approaches to solve DCOPs as well as describe some of our recent extensions of the DCOP model and algorithms. Finally, I will wrap up the talk by briefly describing our recent work on applying DCOP algorithms to solve the problem of scheduling smart/IoT devices in smart homes.
William Yeoh is an assistant professor of computer science at New Mexico State University. He received his Ph.D. in computer science at the University of Southern California. His research interests include multi-agent systems, distributed constraint reasoning, heuristic search, and planning with uncertainty. He is an NSF CAREER awardee and was named in IEEE's AI's 10-to-Watch list in 2015. He currently serves on the editorial board of the Journal of Artificial Intelligence Research.