Sven Koenig is a professor in computer science at the University of Southern California (USC). He received his Ph.D. degree in computer science from Carnegie Mellon University and holds M.S. degrees from the University of California at Berkeley and Carnegie Mellon University. Most of Sven's research centers around techniques for decision making (planning and learning) that enable single situated agents (such as robots or decision-support systems) and teams of agents to act intelligently in their environments and exhibit goal-directed behavior in real-time, even if they have only incomplete knowledge of their environment, imperfect abilities to manipulate it, limited or noisy perception or insufficient reasoning speed. He believes that finding good solutions to these problems requires approaches that cut across many different fields.
Sven is a fellow of the Association for the Advancement of Artificial Intelligence (AAAI) and an ACM Senior Member. He is the recipient of research awards (including an NSF CAREER Award, an IBM Faculty Partnership Award, a Charles Lee Powell Foundation Award and a Raytheon Faculty Fellowship Award) and educational awards (including a Mellon Mentoring Award and an SAIC Student Advisement Award). He was also a program director at the National Science Foundation (NSF) from 2010 to 2012, where he received the Director's Award for Collaborative Integration in both 2011 and 2012. Several of his students won awards as well (including best paper, best dissertation, best research assistant and best teaching assistant awards) and took their first jobs in academia.
Sven has edited several conference proceedings and published more than 150 papers in various areas of artificial intelligence and robotics. He is a councillor of AAAI and was conference co-chair of the 2004 International Conference on Automated Planning and Scheduling, program co-chair of the 2005 International Joint Conference on Autonomous Agents and Multi-Agent Systems and program co-chair of the 2007 and 2008 AAAI Nectar programs. He serves on the editorial boards of Artificial Intelligence, Computational Intelligence, Autonomous Agents and Multi-Agent Systems, AI Magazine and other journals. He serves or served on the advisory, steering or executive committees of the Journal of Artificial Intelligence Research, the International Conference on Automated Planning and Scheduling, the Symposium on Abstraction, Reformulation and Approximation, Americas School on Agents and Multi gent Systems. He co-founded Robotics: Science and Systems, a highly selective robotics conference, in 2005 and subsequently served on both the board of directors and the advisory board of the Robotics: Science and Systems Foundation. He also co-founded the International Symposium on Combinatorial Search, the first regular meeting of the search community in artificial intelligence, in 2009 and now serves on its governing council.
Sven is passionate about helping students and young researchers to get a good start in their careers. He often serves as external member on dissertation committees, was three times co-chair of the AAAI student abstract and poster program, often participates as panelist or mentor in doctoral consortia and frequently presents tutorials on his research at summer schools and conferences. He co-organized many USC Programming Contests and trained USC students for several ACM Programming Competitions.
Additional information on Sven can be found on his webpages: idm-lab.org.
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Planning for Large-Scale Multi-Robot Systems
Multi-robot systems are now being used in industry. For example, hundreds of robots navigate autonomously in Amazon fulfillment centers to move inventory pods all the way from their storage locations...
Cooperative Auctions for Agent or Robot Coordination
Teams of agents are more robust and potentially more efficient than single agents. However, coordinating teams of agents so that they can successfully complete their mission is a challenging...
Making Good Decisions Quickly
Several disciplines, including artificial intelligence, operations research and others, study how to make timely and good decisions. In this talk, I argue that it is possible to combine ideas from these...
Recent Advances in Path Planning
Path planning is an important technology for a large number of applications, and most computer scientists are familiar with Dijkstra's algorithm. In this talk, I discuss recent advances in path...
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