Hyderabad Multi-agent Systems School

(Sponsored by International Foundation for Multiagent Systems, Agents, Theories, Architectures and Languages Workshop, and Autonomous Agents Steering Committee)
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Sven Koenig


Decision Making under Time Pressure and Incomplete Information
            Autonomous agents must be able to make good decisions in complex situations that involve a substantial degree of uncertainty, yet find solutions in a timely manner despite a large number of potential contingencies. Unfortunately, decision making in non-deterministic domains is typically time-consuming due to the large number of contingencies. Thus, autonomous agents need to use decision-making techniques that speed up planning by sacrificing the optimality of the resulting plans, such as agent-centered search and assumption-based planning. In this tutorial, I will give an in-depth overview of such techniques, including algorithms, their analysis using a unifying graph-theoretic framework (including complexity results), and their integration into complete agent architectures. I will then show how these techniques can be used to solve robot-navigation problems, both for single robots and teams of robots. For example, I will show videos of robots that leave trails in the terrain and videos of robots that use auctions for the coordinated exploration of unknown terrain.

Biography
            Sven Koenig is an associate professor in the computer science department of the University of Southern California. He received a Ph.D. degree from Carnegie Mellon University for his thesis on "Goal-Directed Acting with Incomplete Information." He also holds M.S. degrees from the University of California at Berkeley and Carnegie Mellon University.

            Sven is interested in intelligent systems, especially those that have to operate in large, non-deterministic, non-stationary, or only partially known domains. His research centers around techniques for decision making (planning and learning) that enable situated agents (including mobile robots or decision-support systems) to act intelligently in their environments and exhibit goal-directed behavior in real-time, even if they have only incomplete knowledge of their environments, imperfect abilities to manipulate them, limited or noisy perception, or insufficient reasoning speed.

            Sven has edited one book and published over 70 papers in various areas of artificial intelligence and robotics, including papers in IJCAI, AAAI, AAMAS, AIPS, ECP, ICML, COLT, NIPS, KR, ICRA and IROS. He co-chaired the International Conference on Automated Planning and Scheduling in 2004, the Symposium on Abstraction, Reformulation, and Approximation in 2002, various AAAI and AIPS workshops from 1997 to 2000, as well as the Student Abstract and Poster Sessions at the National Conference on Artificial Intelligence (AAAI) in 1999, 2000 and 2002. He has given over 30 invited talks at research institutions as well as tutorials at the National Conference on Artificial Intelligence, the International Conference on Artificial Intelligence Planning Systems, and the International Conference on Robotics and Automation. He is the recipient of an IBM Faculty Partnership Award, an NSF CAREER award, a Raytheon Faculty Fellowship Award, the Tong Leong Lim Pre-Doctoral Prize and a Fulbright Fellowship. He is proud of the fact that several of his students have won awards for their research.


                                                                  Center for Data Engineering, International Institute of Information Technology-Hyderabad .