Brief Bio
Edward H. Shortliffe is Rolf A. Scholdager Professor and Chair of the Department of Biomedical Informatics at Columbia College of Physicians and Surgeons in New York City. He was formerly Professor of Medicine and of Computer Science at Stanford University. After receiving an A.B. in Applied Mathematics from Harvard College in 1970, he moved to Stanford University where he was awarded a Ph.D. in Medical Information Sciences in 1975 and an M.D. in 1976. During the early-1970s, he was principal developer of the medical expert system known as MYCIN. After a pause for internal medicine house-staff training at Massachusetts General Hospital and Stanford Hospital between 1976 and 1979, he joined the Stanford internal medicine faculty where he served as Chief of General Internal Medicine, Associate Chair of Medicine for Primary Care, and directed an active research program in clinical information systems and decision support. He spearheaded the formation of a Stanford graduate degree program in biomedical informatics and divided his time between clinical medicine and biomedical informatics research. In January 2000 he assumed his new post at Columbia University, where he is also Deputy Vice President (Columbia University Medical Center) and Senior Associate Dean (College of Physicians and Surgeons) for Strategic Information Resources, Professor of Medicine, Professor of Computer Science, and Director of Medical Informatics Services for the NewYork-Presbyterian Hospital. He continues to be closely involved with biomedical informatics graduate training and his research interests include the broad range of issues related to integrated decision-support systems, their effective implementation, and the role of the Internet in health care.

Dr. Shortliffe is an elected member of the Institute of Medicine of the National Academy of Sciences (where he currently serves on the IOM executive council), the American Society for Clinical Investigation, the Association of American Physicians, and the American Clinical and Climatological Association. He has also been elected to fellowship in the American College of Medical Informatics and the American Association for Artificial Intelligence. He is a Master of the American College of Physicians (ACP) and was a member of that organization's Board of Regents from 1996-2002. He is Editor-in-Chief of the Journal of Biomedical Informatics, and serves on the editorial boards for several other biomedical informatics publications. He currently sits on the oversight committee for the Division of Engineering and Physical Sciences (National Academy of Sciences) and the Biomedical Informatics Expert Panel (National Center for Research Resources at the National Institutes of Health). He has recently served on the National Committee for Vital and Health Statistics (NCVHS) and on the President's Information Technology Advisory Committee (PITAC). Earlier he served on the Computer Science and Telecommunications Board (National Research Council), the Biomedical Library Review Committee (National Library of Medicine), and was recipient of a research career development award from the latter agency. In addition, he received the Grace Murray Hopper Award of the Association for Computing Machinery in 1976 and has been a Henry J. Kaiser Family Foundation Faculty Scholar in General Internal Medicine. Dr. Shortliffe has authored over 300 articles and books in the fields of medical computing and artificial intelligence. Volumes include Computer-Based Medical Consultations: MYCIN (Elsevier/North Holland, 1976), Readings in Medical Artificial Intelligence: the First Decade (with W.J. Clancey; Addison-Wesley, 1984), Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project (with B.G. Buchanan; Addison-Wesley, 1984), Medical Informatics: Computer Applications in Health Care and Biomedicine (with L.E. Perreault, G. Wiederhold, and L.M. Fagan; Reading, MA: Addison-Wesley, 1990; 2nd edition, New York: Springer-Verlag, 2000), and the third edition of the latter textbook (Biomedical Informatics: Computer Applications in Health Care and Biomedicine, with J.J. Cimino, New York: Springer, 2006.


Abstract
The earliest work in medical artificial intelligence dates to the early 1970s, when the field of AI was about 15 years old. By the end of the decade, the general AI research community was fascinated by the applications being developed in the medical world, noting that significant new AI methods were emerging as AI in Medicine (AIM) researchers struggled with challenging biomedical problems. Over the next decade, the community continued to grow, and with the formation of the Association for the Advancement of Artificial Intelligence in 1980, a special subgroup on medical applications was created. It was against this background that the speaker was asked to address the June 1991 conference of Artificial Intelligence in Medicine Europe (AIME), held in Maastricht, The Netherlands. In that talk, he looked back on AIM progress and anticipated the major challenges for the 1990s. A paper based on that talk was later published (Shortliffe EH. The adolescence of AI in Medicine: Will the field come of age in the '90s? Artif Intell Med 1993;5:93-106). In this presentation, Dr. Shortliffe will reflect on some of the assessments and predictions that arose from his AIME presentation some 18 years ago. He concludes that the AI in Medicine field is robust, albeit less visible than it was in AI's heyday. There is clear evidence of progress, and a community of talented researchers that would benefit from more growth in numbers and in research grant funding. What began largely in the United States in the late 1960s and early 1970s is now a worldwide field, with important contributions from around the globe, but with special acknowledgement to European colleagues who continue to lead us with their biennial AIME conferences and the highly regarded AI in Medicine journal.

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
A swarm-bot is an artifact composed of a swarm of assembled robots called s-bots. The s-bots are mobile robots capable of connecting to, and disconnecting from, other s-bots. S-bots have relatively simple sensors and motors and limited compu- tational capabilities. In the swarm-bot form, the s-bots are attached to each other, forming a single robotic system that can move and change its shape. A swarm-bot can solve problems that cannot be solved by s-bots alone, and is par- ticularly robust to malfunctioning components. In the talk, after shortly describing the s-bots hardware and the methodology we followed to develop algorithms for their control, I will focus on the capabili- ties 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 reconfiguration, distri- buted fault detection and other collective behaviors.

Brief Bio
Prof. Timo Honkela is currently chief scientist at Adaptive Informatics Research Center of Helsinki University of Technology (TKK). The unit is a center of excellence appointed by the Academy of Finland. In the center, Honkela is the head of the Computational Cognitive Systems research group. Earlier he has served as a professor at the laboratory of computer and information science at TKK and as a professor at the Media Lab of University of Art and Design Helsinki. Honkela has approximately one hundred scientific publications. He has conducted research on several areas related to artificial and computational intelligence, cognitive modeling and natural language processing including a central role in the development of the Websom method for visual information retrieval and text mining based on the Kohonen self-organizing map algorithm. Honkela is a former chairman of the Finnish Artificial Intelligence Society and vice-chair of Finnish Cognitive Linguistics Association. He is currently the chair of the IFIP working group on knowledge representation and reasoning (WG 12.1) in which position he has initiated the AKRR conference series on adaptive knowledge representation and reasoning. He has been in a responsible position for a large number of scientific conferences and workshops.

Abstract
It is commonplace to view autonomous agents by considering how much freedom they exhibit in their goal-directed behavior. In other words, the level of motivational autonomy is then in focus. In this presentation, I will discuss, however, why and how the conceptual autonomy of agents is another crucial issue in the field of multiagent system development. In many systems, the agents are provided with a shared conceptual ground. This poses severe limitations for the autonomy of the agents. Namely, it is a reasonable requirement that autonomous agents should be able to interact with each other robustly in open-ended changing environments. As each agent has its own developmental history and as the environments vary to some extent from agent to agent, it is necessary for each agent to build a model of its environment in an individual manner. On the other hand, the agents need to compare these models with each other to enable shared conceptual ground. This can realistically take place through communication in partially shared contexts leading into a sufficient convergence of mapping between the language used by the agents and their individual conceptual systems. In the presentation, I will also discuss what kind of implications these considerations have for the area of artificial intelligence in general.

Brief Bio
Dr. Augusto's research experience since 1998 has been focused on AI-related problems with emphasis on temporal reasoning. His latest research activities have explored the application of spatio-temporal reasoning to Ambient Intelligence (AmI) in general and Smart Homes in particular. He has edited two books in the area ("Designing Smart Homes" by Springer Verlag and "Advances in Ambient Intelligence" by IOS Press). He has contributed to the research community with more than 70 publications and various invited talks and tutorials (including those at IJCAI'07 and AAAI'08). He has been co-chair of the 4th International Conference on Smart Homes and Telecare and co-chair of the three editions of AITAmI (a workshop focused on the role of AI in AmI). Recently he has been appointed as Editor in Chief of the Book Series on "Ambient Intelligence and Smart Environments" and co-Editor in Chief of the "Journal on Ambient Intelligence and Smart Environments (JAISE)", both published by IOS Press.


Abstract
Ambient Intelligence is growing fast as a multi-disciplinary area which promises to have a real beneficial influence in our society and to revolutionize the way people interacts with computing. The basic idea is that by enriching an environment with technology (sensors and devices interconnected through networks), a Smart Environment, systems can be built such that information gathered in real-time and historical data accumulated can be used to support decisions that benefit the users of that environment. An examples of such environments are Smart Homes, probably the most well-known and well-advertised realization of the concept of Ambient Intelligence. But other applications are feasible and equally relevant (e.g., smart cars, smart classrooms, smart offices, a shopping centre, a street, etc.). All these environments can be equipped in such a way that they cooperate to improve safety, comfort and efficiency of the people interacting with them. This talk will describe the characteristics of these systems, provide examples of applications and highlight the challenges and opportunities ahead for the intended audience of ICAART'09.

Brief Bio
Paulo Urbano finished graduation on Computer Science in 1990, from Universidade de Coimbra, received the Masters on Computer Science in 1994, from Universidade Nova de Lisboa, and the doctoral degree in Computer Science in 2004 from Universidade de Lisboa. He is an assistant professor in Departamento de Informática da Faculdade de Ciências da Universidade de Lisboa. He is a member of the LabMag (a research lab on multi-agents systems). His current research interests include Creative Artificial Systems, Collective artificial Art, swarm intelligence, swarm robotics, social simulation and multi-agent systems coordination. He is the scientific coordinator of NADA magazine which publishes articles related to Art and Science.


Abstract
As we can easily imagine it is easy for a group of non-coordinated artificial agents to produce a chaotic artistic pattern. I will discuss the importance of multi-agent coordination in the formation of collective artistic patterns. Artificial Life has been a recent inspiration in the media arts, specially the concepts of self- organization, evolution and behavior based robotics. The study of self- organization has revealed that numerous sophisticated pattern formation, decision making and collective behavior are the emergent result of very simple behaviors performed by masses of individuals relying only on local information. I will speak about my experience in designing societies composed by a large number of very simple micro- painters that have very limited perception and communication abilities that try to coordinate and make emerge a collective digital painting. I will focus on direct and indirect forms of communication for achieving coordination. I will begin describing the estigmergic micro-painters, which are coordinated by the patterns that they are producing. The work they are making, changing the environment, influence the other's activities. I will also also present self-organised direct coordination based on mimetic forms of interaction, where micro-agents can make collective consensual decisions regarding their movement inside the canvas and the selection of color, making emerge aesthetically interesting patterns.