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Invited Speakers


Wednesday, May 14th, 8:40-9:40

Demetri Terzopoulos (bio)
     Autonomous Virtual Humans and Lower Animals: From Biomechanics to Intelligence (abstract)

Thursday, May 15th, 8:40-9:40

Moshe Tennenholtz (bio)
     Game-Theoretic Recommendations: Some Progress in an Uphill Battle (abstract) (slides)

Thursday, May 15th, 17:30-18:30

Yoav Shoham (ACM-SIGART Award Talk) (bio)
     Computer Science and Game Theory (abstract)

Friday, May 16th, 8:40-9:40

Randy Beard (bio)
     Cooperative Control of Small and Micro Air Vehicles (abstract)

 


Demetri Terzopoulos bio:

Demetri Terzopoulos is the Chancellor's Professor of Computer Science at the University of California, Los Angeles. He graduated from McGill University and obtained his PhD degree from MIT ('84). He is a Fellow of the ACM, a Fellow of the IEEE, a Fellow of the Royal Society of Canada, and a member of the European Academy of Sciences. His many awards and honors include an Academy Award for Technical Achievement from the Academy of Motion Picture Arts and Sciences for his pioneering work on physics-based computer animation, and the inaugural Computer Vision Significant Researcher Award from the IEEE for his pioneering and sustained research on deformable models and their applications. He is listed by ISI and other indexes as one of the most highly-cited authors in engineering and computer science, with more than 300 published research papers and several volumes, primarily in computer graphics, computer vision, medical imaging, computer-aided design, and artificial intelligence/life. Professor Terzopoulos joined UCLA in 2005 from New York University, where he held the Lucy and Henry Moses Professorship in Science and was Professor of Computer Science and Mathematics at NYU's Courant Institute. Previously he was Professor of Computer Science and Professor of Electrical and Computer Engineering at the University of Toronto, where he currently retains status-only faculty appointments. www.cs.ucla.edu/~dt

Abstract (Autonomous Virtual Humans and Lower Animals: From Biomechanics to Intelligence)

The confluence of virtual reality and artificial life, an emerging discipline that spans the computational and biological sciences, has yielded synthetic worlds inhabited by realistic artificial flora and fauna. Artificial animals are complex synthetic organisms that have functional, biomechanical bodies, perceptual sensors, and brains with locomotion, perception, behavior, learning, and cognition centers. Virtual humans and lower animals are of interest in computer graphics because they are self-animating graphical characters poised to dramatically advance the interactive game and motion picture industries even more so than have physics-based simulation technologies. More broadly, these biomimetic autonomous agents in their realistic virtual worlds also foster deeper computationally-oriented insights into natural living systems. Furthermore, they engender interesting applications in computer vision, sensor networks, archaeology, and other domains.


Moshe Tennenholtz bio:

Moshe Tennenholtz is a professor with the faculty of Industrial Engineering and Management at the Technion--Israel Institute if technology, where he holds the Sondheimer Technion Academic Chair. During 1999-2002 he has been a visiting professor at Stanford CS department, where he has also been a research associate during the years 1991-1993. Moshe received his B.Sc. in Mathematics from Tel-Aviv University (1986), and his M.Sc. and Ph.D. (1987, 1991) from the Department of Applied Mathematics and Computer Science in the Weizmann Institute. Moshe served as the editor-in-chief of the Journal of Artificial Intelligence Research [JAIR]; he is an associate editor of Games and Economic Behavior, and of the international journal of autonomous agents and multi-agent systems, and an editorial board member of the Journal of Machine Learning Research [JMLR]. In joint work with colleagues and students he introduced several contributions to the interplay between computer science and game theory, such as the study of artificial social systems, co-learning, non-cooperative computing, distributed games, the axiomatic approach to qualitative decision making, the axiomatic approach to ranking, reputation, and trust systems, competitive safety analysis, program equilibrium, mediated equilibrium, and learning equilibrium.

Abstract (Game-Theoretic Recommendations: Some Progress in an Uphill Battle)

In this talk we consider two highly challenging problems in the foundations of game theory and its application to multi-agent systems. Namely, we consider the question of how should an agent choose its action in a given game, and the task of leading agents to adopt desired behaviors in a given game. In the recent years we provided some useful attacks on these fundamental problems. Our study of competitive safety analysis and the study of learning in ensembles of games, provide surprisingly useful tools for addressing the first challenge. Our theory of mediators provides powerful tools for addressing the second challenge. These approaches refer to non-cooperative games; in the context of social choice, we introduced the axiomatic approach to ranking/reputation/trust/recommendation systems; in particular, our work on trust-based recommendation systems introduces several basic results in the characterization of useful recommendation techniques.

Click here to download the slides from the presentation.


Yoav Shoham bio:

Yoav Shoham is Professor of Computer Science at Stanford University, where he has been since receiving his PhD in Computer Science from Yale University in 1987 and spending an abbreviated post-doctoral position at the Weizmann Institute of Science. He has worked in various areas of AI, including temporal reasoning, nonmonotonic logics and theories of commonsense. Shoham's interest in recent years has been multiagent systems, and in particular the interaction between computer science and game theory. Shoham is a Fellow of the Association for Advancement of Artificial Intelligence (AAAI), and charter member of the International Game Theory Society. He is an author of four books, an editor of one, and an author of numerous articles. He is also a founder of several successful e-commerce software companies.

Abstract (Computer Science and Game Theory)

Game theory has been playing an increasingly visible role in computer science, in areas as diverse as artificial intelligence, theory, distributed systems, and other areas. I take stock of where most of the action has been in the past decade or so, and suggest that going forward, the most dramatic interaction between computer science and game theory could be around what might be called game theory pragmatics.


Randy Beard bio:

Randal W. Beard received the B.S. degree in electrical engineering from the University of Utah, Salt Lake City, in 1991, the M.S. degree in electrical engineering in 1993, the M.S. degree in mathematics in 1994, and the Ph.D. degree in electrical engineering in 1995, all from Rensselaer Polytechnic Institute, Troy, N.Y. Since 1996, he has been with the Electrical and Computer Engineering Department at Brigham Young University, Provo, UT, where he is currently a professor. In 1997 and 1998, he was a Summer Faculty Fellow at the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA. In 2006-2007 he was a National Research Council Fellow at the Air Force Research Labs at Eglin Air Force Base, Fort Walton Beach, Florida, where he worked on vision based guidance and control algorithms for micro air vehicles.

His primary research focus is in autonomous systems, unmanned air vehicles, and multiple vehicle coordination and control. He has published over 40 journal articles and over 90 peer reviewed conference articles and has received funding from AFOSR, AFRL, NASA, DARPA, and NSF.

He is a senior member of the IEEE and the AIAA. He is an editor for the Journal of Intelligent and Robotics Systems, and an associate editor for the IEEE Control Systems Magazine. In 1998 and 2004 he was voted the outstanding teacher in the BYU Electrical and Computer Engineering Department by graduating seniors, and in 2002 he received the Outstanding Professor award from the BYU Electrical and Computer Engineering Department. In 2004 he was awarded the BYU Young Scholar Award and in 2006 he was awarded the BYU Technology Transfer Award. His students have won numerous competitions and awards for their work on micro air vehicles.

Abstract (Cooperative Control of Small and Micro Air Vehicles)

The focus of this talk will be cooperative control techniques for small and micro air vehicles. There are numerous potential applications of this technology including aerial reconnaissance, border patrol, monitoring forest fires, oil fields, and pipelines, and tracking wildlife. This talk will present a general approach to cooperative control problems which can be summarized in four steps. The first step is to identify the coordination variables which are the minimal information needed to effect cooperation. The second step is to quantify the cooperation constraint and cooperation objective in terms of the coordinate variables. The third step is to develop a centralized cooperation strategy that acts upon the instantaneous values of the coordination variables to achieve the objectives. Finally, the fourth step is to use information consensus schemes to transform the centralized strategy into a decentralized algorithm. The consensus algorithms allow a team of vehicles to agree upon the instantaneous value of the coordination variables while connected through a noisy, intermittent, time-varying communication network.

We will also show several applications of our approach in the context of small unmanned air vehicles (UAVs). The first application will be to the problem of cooperative rendezvous. There are numerous military scenarios where it is desirable to have a team of UAVs converges simultaneously to a region of interest. However, pop-up threats, wind, and an unreliable communication environment make this problem extremely challenging for small UAVs. The second application will be distributed fire perimeter monitoring where a team of UAVs is tasked to monitor the border of a forest fire. The nature of the environment only allows communication when the UAVs are in close vicinity of each other. Therefore, cooperation must be achieved with only infrequent communication. The third application will be that of cooperatively tracking and targeting a moving ground target when sensor occlusions are probable.

   
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