Les conférences invitées ont lieu au cours de sessions communes accessibles à toutes les conférences. Les participants ont ainsi l'occasion de découvrir des travaux récents de chacune des communautés.
|Aldo Gangemi - Professeur (Université Paris Nord, France)|
|Nicola Guarino - Directeur de Recherche (CNR, Italie)
Title: 25 Years of Applied Ontology and Ontological Analysis: an Interdisciplinary Endeavour
Abstract: Applied Ontology is an emerging discipline –born about 25 years ago– that builds on philosophy, cognitive science, linguistics and logic with the purpose of understanding, clarifying, making explicit and communicating people’s assumptions about the nature and structure of the world. This orientation towards helping people understanding each other distinguishes applied ontology from philosophical ontology, and motivates its unavoidable interdisciplinary nature. In this talk I will briefly review the problems that applied ontology can address, the conceptual tools at the basis of formal ontological analysis, and the future application perspectives.
Short biography: Nicola Guarino, research director at the Italian National Research Council (CNR), works at the nation-wide Institute of Cognitive Sciences and Technologies (ISTC-CNR), leading the Laboratory for Applied Ontology (LOA) located in Trento. A graduate in electronic engineering at Padua university in 1978, since 1991 has been playing a leading role in the ontology field, developing a strongly interdisciplinary approach that combines together Computer Science, Philosophy, and Linguistics. His impact is testified by a long list of widely cited papers and many keynote talks and tutorials in major conferences involving different communities. Among the most well known results of his lab, the OntoClean methodology and the DOLCE foundational ontology. On the theoretical side, current research interest include the formal ontology of relationships and events, while on the application side his research is focusing on service science, socio-technical systems, and e-government. He is founder and former editor-in-chief (with Mark Musen of Stanford University) of Applied Ontology, founder and past president of the International Association for Ontology and its Applications, former general chair of the international conference on Formal Ontology in Information Systems (FOIS), editorial board member of Journal of Data Semantics, and editor of the IOS Press book series Frontiers in AI and Applications. He is also fellow of the European Coordinating Committee for Artificial Intelligence (ECCAI).
|Daniela Rus - Professeur (MIT, USA)|
|Zhongzhi Shi - Directeur de Recherche (CAS, Chine)
Title: Brain Machine Integration
Abstract: Intelligence Science is an interdisciplinary subject which dedicates to joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. Brain science explores the essence of brain, research on the principle and model of natural intelligence in molecular, cell and behavior level. Cognitive science studies human mental activity, such as perception, learning, memory, thinking, consciousness etc. In order to implement machine intelligence, artificial intelligence attempts simulation, extension and expansion of human intelligence using artificial methodology and technology. At present, brain machine integration is an active research area which aims to develop an unified, universal intelligent system. This lecture will explore the cognitive model of brain machine integration, introduce environment awareness, motivation driven automated reasoning and collaborative decision making. Finally, I briefly introduce the research on brain science and brain-inspired intelligence in China.
Short biography: Zhongzhi Shi, Professor at the Institute of Computing Technology, Chinese Academy of Sciences. Fellow of CCF and CAAI. IEEE senior members, AAAI, ACM members. His research interests mainly contain intelligence science, artificial intelligence, multi-agent systems, machine learning. He has been responsible for 973, 863, key projects of NSFC. He has been awarded with various honors, such as National Science and Technology Progress Award (2012), Beijing Municipal Science and Technology Award (2006), the Achievement Award of Wu Wenjun artificial intelligence science and technology by CAAI (2013), the Achievement Award of Multi-Agent Systems by China Multi-Agent Systems Technical Group of AIPR, CCF (2016). He has published 16 books, including "Mind Computation", "Intelligence Science", "Advanced Artificial Intelligence", "Principles of Machine Learning". Published more than 500 academic papers. He served as chair of the machine learning and data mining group, IFIP TC12. He served as Secretary-General of China Computer Federation, vice chair of China Association of Artificial Intelligence.
|Moshe Vardi - Professeur - Université Rice - USA
Title: The Automated-Reasoning Revolution: From Theory to Practice and Back
Abstract: For the past 40 years computer scientists generally believed that NP-complete problems are intractable. In particular, Boolean satisfiability (SAT), as a paradigmatic automated-reasoning problem, has been considered to be intractable. Over the past 20 years, however, there has been a quiet, but dramatic, revolution, and very large SAT instances are now being solved routinely as part of software and hardware design. In this talk I will review this amazing development and show how automated reasoning is now an industrial reality. I will then describe how we can leverage SAT solving to accomplish other automated-reasoning tasks. Counting the the number of satisfying truth assignments of a given Boolean formula or sampling such assignments uniformly at random are fundamental computational problems in computer science with applications in software testing, software synthesis, machine learning, personalized learning, and more. While the theory of these problems has been thoroughly investigated since the 1980s, approximation algorithms developed by theoreticians do not scale up to industrial-sized instances. Algorithms used by the industry offer better scalability, but give up certain correctness guarantees to achieve scalability. We describe a novel approach, based on universal hashing and Satisfiability Modulo Theory, that scales to formulas with hundreds of thousands of variables without giving up correctness guarantees.
Short biography: Moshe Y. Vardi is the George Distinguished Service Professor in Computational Engineering and Director of the Ken Kennedy Institute for Information Technology at Rice University. He is the recipient of three IBM Outstanding Innovation Awards, the ACM SIGACT Goedel Prize, the ACM Kanellakis Award, the ACM SIGMOD Codd Award, the Blaise Pascal Medal, the IEEE Computer Society Goode Award, the EATCS Distinguished Achievements Award, and the Southeastern Universities Research Association's Distinguished Scientist Award. He is the author and co-author of over 500 papers, as well as two books: "Reasoning about Knowledge" and "Finite Model Theory and Its Applications". He is a Fellow of the Association for Computing Machinery, the American Association for Artificial Intelligence, the American Association for the Advancement of Science, the European Association for Theoretical Computer Science, the Institute for Electrical and Electronic Engineers, and the Society for Industrial and Applied Mathematics. He is a member of the US National Academy of Engineering and National Academy of Science, the American Academy of Arts and Science, the European Academy of Science, and Academia Europaea. He holds honorary doctorates from the Saarland University in Germany, Orleans University in France, UFRGS in Brazil, and the University of Liege in Belgium. He is currently a Senior Editor of of the Communications of the ACM, after having served for a decade as Editor-in-Chief.