Brief Bio
Marco Dorigo received the Laurea (Master of Technology) degree in industrial technologies engineering in 1986 and the doctoral degree in information and systems electronic engineering in 1992 from Politecnico di Milano, Milan, Italy, and the title of Agrégé de l'Enseignement Supérieur, from the Université Libre de Bruxelles, Belgium, in 1995. From 1992 to 1993 he was a research fellow at the International Computer Science Institute of Berkeley, CA. In 1993 he was a NATO-CNR fellow, and from 1994 to 1996 a Marie Curie fellow. Since 1996 he has been a tenured researcher of the FNRS, the Belgian National Fund for Scientific Research, and a research director of IRIDIA-CoDE, the artificial intelligence laboratory of the Université Libre de Bruxelles. He is the inventor of the ant colony optimization metaheuristic. His current research interests include swarm intelligence, swarm robotics, and metaheuristics for discrete optimization. Dr. Dorigo is the Editor-in-Chief of the Swarm Intelligence journal. He is an Associate Editor for the IEEE Transactions on Evolutionary Computation, the IEEE Transactions on Systems, Man, and Cybernetics, and the ACM Transactions on Autonomous and Adaptive Systems. He is a member of the Editorial Board of numerous international journals, including: Adaptive Behavior, AI Communications, Artificial Life, Cognitive Systems Research, Evolutionary Computation, Information Sciences, Journal of Heuristics and Journal of Genetic Programming and Evolvable Machines. In 1996 he was awarded the Italian Prize for Artificial Intelligence, in 2003 the Marie Curie Excellence Award, and in 2005 the Dr A. De Leeuw-Damry-Bourlart award in applied sciences. He is a fellow of the IEEE and of the ECCAI, the European Coordinating Committee for Artificial Intelligence.


Abstract
Swarm intelligence is the discipline that deals with natural and artificial sys- tems composed of many individuals that coordinate using decentralized control and self-organization. In particular, it focuses on the collective behaviors that result from the local interactions of the individuals with each other and with their environment. The characterizing property of a swarm intelligence sys- tem is its ability to act in a coordinated way without the presence of a coordi- nator or of an external controller. Swarm robotics could be defined as the application of swarm intelligence princi- ples to the control of groups of robots.
In this talk I will discuss results of Swarm-bots, an experiment in swarm robo- tics. A swarm-bot is an artifact composed of a swarm of assembled s-bots. The s-bots are mobile robots capable of connecting to, and disconnecting from, other s-bots. In the swarm-bot form, the s-bots are attached to each other and, when needed, become a single robotic system that can move and change its shape. S-bots have relatively simple sensors and motors and limited computational capa- bilities. A swarm-bot can solve problems that cannot be solved by s-bots alone. In the talk, I will shortly describe the s-bots hardware and the methodology we followed to develop algorithms for their control. Then I will focus on the capa- bilities of the swarm-bot robotic system by showing video recordings of some of the many experiments we performed to study coordinated movement, path formation, self-assembly, collective transport, shape formation, and other collective beha- viors.

Brief Bio
Dr. Peter Simon Sapaty, educated as power networks engineer, is with distributed systems for 40 years, implementing heterogeneous computer networks from the end of the sixties. Being chief research scientist and director of distributed simulation and control at the Institute of Mathematical Machines and Systems, National Academy of Sciences of Ukraine, also worked in Czechoslovakia, Germany, UK, Canada, and Japan as project leader, research professor, department head, and special invited professor; chaired a special interest group on mobile cooperative technologies within Distributed Interactive Simulation project in the US. Peter invented and prototyped a distributed networking technology (supported by Siemens/Nixdorf, Ericsson UK, and Japan Society for the Promotion of Science) used in different countries and resulted in a European Patent and two John Wiley books. His interests include models and languages for coordination and simulation of distributed dynamic systems with application in intelligent network control, emergency management, infrastructure protection, and cooperative robotics.


Abstract
We are witnessing rapid growth of world dynamics caused by consequences of global warming, globalization of economy, numerous ethnic, religious and military conflicts, and international terrorism. To match this dynamics and withstand numerous threats and possible adversaries, effective integration of any available human and technical resources is crucial. These resources may be scattered and emergent, lacking the infrastructures and authorities for organization of the solutions needed, in real time and ahead of it. Just communication between predetermined parts and systems with sharing a common vision, often called "interoperability", may not be sufficient. The whole distributed system should rather represent a highly dynamic and integral organism, in which parts may be defined and interlinked dynamically in subordination to the global organization and system goals, which can vary at runtime, with the coined term "overoperability" [1] becoming more appropriate.

A novel ideology and technology meeting these objectives will be presented, based on a special high-level World Processing Language (WPL) describing what to do in distributed spaces rather than how to do, and by which resources (or even system organization), leaving these to automatic interpretation in networked environments. This (parallel and fully distributed, without any central resources) process can constantly take into account peculiarities of the environments in which mission scenarios evolve. The WPL scenarios, navigating the systems to be managed and covering ("conquering") them at runtime, are integral and compact, capable of self-recovery after damages, and may be created on the fly, as traditional synchronization, data, code, and agents handling and exchanges are effectively shifted to the implementation.

The details of WPL and its distributed cooperative implementation will be revealed, with communicating interpreters to be installed in internet hosts, mobile robots, mobile phones, or smart sensors. The language interpreters may be concealed and can migrate in unpredictable environments, collectively executing (also mobile) mission scenarios, resulting altogether in a flexible and ubiquitous overall system organization dominating over other systems and actually converting the whole world into a dynamic supercomputer capable of solving any problems on itself, with the teaming "processors" being both human and technical. Navigating in distributed worlds, the WPL scenarios can dynamically create distributed knowledge networks that can be effectively used for command and control, global situation awareness, and making automated (up to fully automatic) decisions.

This patented technology [2] has been successfully used (or being suitable) for distributed knowledge bases, distributed inference and making decisions in semantic networks, solving distributed graph and network problems, intelligent network management, distributed virtual reality (see [3] for all these), distributed simulation of dynamic systems like battlefields or road networks [3, 4], collective behavior of robots and infrastructure protection [5], emergency management [6], flexible command and control [7], distributed management of directed energy and electronic warfare systems [8, 9], and finding global solutions by smart sensor networks [10].

Many application code examples in WPL will be demonstrated in the lecture, especially those dealing with dynamic mission scenarios in distributed physical and virtual spaces, flexible command and control, protecting critical infrastructures and key resources (while destroying the malicious ones, if required), collective behavior of robots (ranging from loose swarm behavior to hierarchically controlled goal-directed missions), unified human-robotic integration, and global fighting of illegal intrusions in computer networks.

[1] P.S. Sapaty, "Over-Operability in Distributed Simulation and Control", The MSIAC's M&S Journal Online, Winter 2002 Issue, Volume 4, No. 2, Alexandria, VA, USA, 9p.
[2] P. S. Sapaty, A distributed processing system. European Patent No. 0389655, Publ. 10.11.93, European Patent Office.
[3] P. S. Sapaty, Mobile processing in distributed and open environments. John Wiley & Sons, ISBN: New York, February 1999.
[4] P. S. Sapaty, M. J. Corbin, S. Seidensticker, Mobile intelligence in distributed simulations. Proc. 14th Workshop on Standards for the Interoperability of Distributed Simulations, IST UCF, Orlando, FL, March 1995.
[5] P. S. Sapaty, Ruling distributed dynamic worlds. John Wiley & Sons, New York, May 2005.
[6] P. Sapaty, M. Sugisaka, R. Finkelstein, J. Delgado-Frias, N. Mirenkov, Advanced IT support of crisis relief missions. Journal of Emergency Management, Vol.4, No.4, July/August 2006.
[7] P. Sapaty, A. Morozov, R. Finkelstein, M. Sugisaka, D. Lambert, A new concept of flexible organization for distributed robotized systems. Proc. Twelfth International Symposium on Artificial Life and Robotics (AROB 12th'07), Beppu, Japan, Jan 25-27, 2007.
[8] P. Sapaty, A. Morozov, M. Sugisaka, DEW in a network enabled environment. Proc. international conference Directed Energy Weapons 2007, Feb. 28 - March 1, 2007, Le Meridien Piccadilly, London, UK.
[9] P. Sapaty, Global management of distributed EW-related systems, In: Electronic Warfare: Operations & Systems 2007, 19-20 Sept. 2007, Thistle Selfridge, London, UK.
[10] P. Sapaty, Intelligent management of distributed sensor networks. In: Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense VI, edited by Edward M. Carapezza, Proc. of SPIE Vol. 6538, 653812, (2007).

Brief Bio
Ronald C. Arkin is Regents' Professor and the Director of the Mobile Robot Laboratory in the College of Computing at the Georgia Institute of Technology. He has held visiting positions at the Royal Institute of Technology in Stockholm, the Sony Intelligence Dynamics Laboratory in Tokyo, and LAAS/CNRS in Toulouse. Dr. Arkin's research interests include behavior-based reactive control and action-oriented perception for mobile robots and unmanned aerial vehicles, hybrid deliberative/reactive software architectures, robot survivability, multiagent robotic systems, biorobotics, human-robot interaction, robot ethics, and learning in autonomous systems. He has over 130 technical publications in these areas and has written a textbook entitled Behavior-Based Robotics and is the Series Editor for the MIT Press book series Intelligent Robotics and Autonomous Agents. Prof. Arkin served two terms on the Administrative Committee of the IEEE Robotics and Automation Society, serves as the co-chair of the IEEE RAS Technical Committee on Robot Ethics, and also served on the National Science Foundation's Robotics Council. He was elected a Fellow of the IEEE in 2003, and is a member of AAAI and ACM.


Abstract
In the Summer of 2005, a significant research effort was conducted at Sony's Intelligence Dynamics Laboratory (SIDL), involving personnel from Georgia Tech, MIT, CMU, Osaka University, and SIDL, working towards the implementation of a theory of designed development for a humanoid robot. This research involves numerous insights gleaned from cognitive psychology (drawn from both new and old theories of behavior) and integrating these techniques into Sony's humanoid robot QRIO architecture with the long-term goal of providing highly satisfying long-term interaction and attachment formation by a human partner. The underlying models used and the results obtained on QRIO are presented.

Brief Bio
Miguel Ayala Botto received the master degree in Mechanical Engineering in 1992 and the Ph.D. in Mechanical Engineering in 1996 from Instituto Superior Técnico, Tecnhical University of Lisbon, Portugal. He spent the year of 1995 at the Control Laboratory, Department of Electrical Engineering, Delft University of Technology, Holland. Further, in the winter semester of the academic year 1999/2000 he held a postdoctoral position at the same laboratory. Since 2001 he is Associate Professor at the Department of Mechanical Engineering, Instituto Superior Técnico, Portugal. He is currently coordinator of the research group on Systems and Control from the Center of Intelligent Systems of IDMEC - Institute of Mechanical Engineering. Since 2005 he is the head of the Portuguese Association on Automatic Control, the National Member Organization from IFAC. He has published more than 70 journal papers, book chapters, and communications in international conferences. He has been awarded in 1999 with "The Heaviside Premium", attributed by the Council IEE - The Institution of Electrical Engineers, UK. Currently he is Associate Editor of the International Journal of Systems Science (Taylor & Francis) and member of the IFAC Technical Committee on Discrete Event and Hybrid Systems. His main research interest is in the field of estimation and control of hybrid dynamical systems.


Abstract
Hybrid systems are dynamical systems composed by both discrete valued and continuous states. The dynamics of a hybrid system is governed by a mode selector that determines, at each time instant, which discrete mode is active from endogenous and/or exogenous variables. The continuous state is then updated through a dynamic relation that is selected from a set of possible dynamics according to the value of the active discrete mode. This interaction can be found in many real world applications, embedded control systems, and in the control of complex industrial systems via the combination of classical continuous control laws with supervisory switching logic.

Most of the available hybrid controllers design techniques do not explicitly consider either state or mode uncertainty in the hybrid model. Specially in real harsh industrial environments with a strong presence of noisy channels, and possibly actuators/sensors failures, the explicit consideration of uncertainty should not be neglected. However, the introduction of a stochastic nature to the hybrid model increases its level of complexity which may well compromise the global performance of the hybrid controller due to wrong state and/or mode estimations.

This keynote will focus on the relevant issues and main approaches to the state and mode estimation of stochastic hybrid systems. The ideas will be further applicable to Fault Detection and Isolation (FDI) classical problems.