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Colloquium – Hang Ma
April 1 @ 10:00 am - 11:00 am
University of Southern California
April 1, 2019
lecture – 10:00am
Host: Rogelio Cardona-Rivera
Intelligent Task and Path Planning for Teams of Agents
Teams of agents must often assign tasks among themselves and plan collision-free paths to the task locations. Examples include autonomous aircraft towing vehicles, automated warehouse systems, office robots, and game characters in video games. In the near future, autonomous aircraft towing vehicles will tow aircraft all the way from the runways to their gates (and vice versa), thereby reducing pollution, energy consumption, congestion, and human workload. Today, hundreds of robots already navigate autonomously in Amazon fulfillment centers to move inventory pods all the way from their storage locations to the inventory stations that need the products they store. Coordination problems for these teams of agents are NP-hard in general, yet we must make fast and good decisions when it comes to assigning tasks and finding collision-free paths for these teams of agents. Better task assignment and shorter paths result in higher throughput or lower operating costs (since fewer robots are required).
In this context, (1) I will describe several versions of task-assignment and path-planning problems for teams of agents, their complexities, algorithms for solving them, and their applications; and (2) I will present an algorithmic framework that unifies tools and techniques from artificial intelligence, robotics, operations research, and theoretical computer science to coordinate long-term operations for real-world multi-agent systems at a scale of hundreds of agents and thousands of tasks.
Hang Ma is a Ph.D. candidate at the University of Southern California. He holds a B.Sc. (First Class with Distinction) in Computing Science from Simon Fraser University, a B.Eng. in Computer Science and Technology from Zhejiang University (jointly with Simon Fraser University), and an M.Sc. in Computer Science from McGill University. His research interests lie in artificial intelligence, robotics, and machine learning, with a focus on decision making for multi-agent systems. He is a winner of the Outstanding Paper Award in the Robotics Track of the International Conference on Automated Planning and Scheduling 2016 and a USC Annenberg Graduate Fellowship. More information can be found on his webpage: http://www-scf.usc.edu/~hangma/.