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Keynote Lectures

The Complexity Crisis
François E. Cellier, Independent Researcher, Switzerland

Context-Aware Decision Support in Dynamic Environments - Theoretical & Technological Foundations
Alexander Smirnov, SPC RAS, Russian Federation


The Complexity Crisis

François E. Cellier
Independent Researcher

Brief Bio
François E. Cellier received his BS degree in electrical engineering in 1972, his MS degree in automatic control in 1973, and his PhD degree in technical sciences in 1979, all from the Swiss Federal Institute of Technology (ETH) Zurich. Dr. Cellier worked at the University of Arizona as professor of Electrical and Computer Engineering from 1984 until 2005. He returned to his home country of Switzerland and his alma mater in the summer of 2005.Dr. Cellier's main scientific interests concern modeling and simulation methodologies, and the design of advanced software systems for simulation, computer-aided modeling, and computer-aided design. Dr. Cellier has authored or co-authored more than 200 technical publications, and he has edited several books. He published a textbook on Continuous System Modeling in 1991 and a second textbook on Continuous System Simulation in 2006, both with Springer-Verlag, New York. He is a fellow of the Society for Modeling and Simulation International (SCS).

Engineering systems are becoming ever more complex. The total length of the wires in the cable tree of a modern jetliner adds up to several hundred kilometers. The cable tree features many thousand connections. These systems have become so complex that it is no longer possible to completely test such a system ahead of time in all of its
potential operational modes. Simulation may offer a partial answer to the problem, but also the models of these systems are becoming ever more complex.

The talk will address a variety of issues related to these problems:
1. What demands are to be met by modeling environments to enable modelers to formulate models of complex systems reliably and within reasonable time limits?
2. What demands are to be met by simulation environments to enable them to simulate large-scale models of complex physical systems reliably, effectively, and efficiently?
3. How can models of complex systems become fault-tolerant, i.e., what demands must models meet such that simulations can recover from errors on their own when they get into trouble during simulation?



Context-Aware Decision Support in Dynamic Environments - Theoretical & Technological Foundations

Alexander Smirnov
Russian Federation

Brief Bio
Alexander Smirnov is a Head of Computer Aided Integrated Systems Laboratory, St. Petersburg Federal Research Center of the Russian Academy of Sciences (SPC RAS). He received his Ph.D from St. Petersburg State University of Electrical Engineering (1984) and Dr.habil. from St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (1994), and became a Full Professor in 1998. Also, he is a Professor and a Head of International Laboratory on Intelligent Technologies for Socio-Cyberphysical Systems, ITMO University, St. Petersburg (from 2014), and a Founder of Joint Master Program on Business Informatics between ITMO University and Rostock University (Germany). He has been involved in projects sponsored by Ford, Nokia, Festo, US DoD, European Research Programs (Information Society Technologies, Esprit, Eureka/Factory, etc.), and Russian agencies in the areas of distributed intelligent systems, ontology management, intelligent decision support systems, etc.

Context-aware decision support is required in situations happening in dynamic, rapidly changing, and often unpredictable distributed environments. Such situations can be characterized by highly decentralized up-to-date data sets coming from various resources located in cyber-physical space. The goals of context-aware support of operational decision making are to timely provide the decisions maker with up-to-date information, to assess the relevance of information & knowledge to a decision, and to gain insight in seeking and evaluating possible decision alternatives.
The lecture addresses theoretical and technological foundations of context-aware decision support. The theoretical fundamentals are built around ontologies as a widely accepted tool for the semantic modeling of context information. They provide efficient facilities to represent application knowledge, and to make resources of the dynamic environments context-aware and interoperable.
The proposed fundamentals are supported by advanced intelligent technologies (ontology management, context management, constraint satisfaction, smart space, and decision mining). An application of these ideas is illustrated by examples of decision support systems for dynamic logistics.