The creative process, for centuries, has been infused with an element of magic, an unexplainability that is supposed to elevate some human minds above the rest - and certainly above mere machines. But creative ideas are, first and foremost, ideas. A fundamental axiom of AI is that the production of ideas can be explained as symbol manipulation and can be reproduced with a symbol manipulation machine. Thus we should be prepared to offer a model of the computational mechanisms by which creative ideas are produced. Some work in psychology and some AI programs suggest mechanisms we will explore as candidates for a model of creativity.
Bruce Buchanan is University Professor of Computer Science Emeritus, and former Professor of Philosophy, Medicine, and Intelligent Systems at the University of Pittsburgh. He is a member of the National Academy of Science Institute of Medicine and has also served as President and Secretary-Treasurer of the AAAI. His main research interests are in machine learning, knowledge-based systems, medical expert systems, and computational biology, and is generally interested in applications of machine learning and artificial intelligence to problems in biology or medicine. His recent research includes: AI approaches to machine learning and discovery, applications of symbolic learning to problems in biology and medicine, and case-based reasoning with application to prediction of protein secondary structure.
Personalized interaction with computer systems can be at odds with privacy since it necessitates the collection of considerable amounts of personal data. Numerous consumer surveys revealed that computer users are very concerned about their privacy online. The collection of personal data is also subject to legal regulations in many countries and states. This talk presents work in the area of Privacy- Enhanced Personalization that aims at reconciling personalization with privacy through suitable human-computer interaction strategies and privacy-enhancing technologies.
Alfred Kobsa is a Professor in the Donald Bren School of Information and Computer Sciences of the University of California, Irvine. Before he was a Director of the Institute for Applied Information Technology (FIT) at the German National Research Center for Information Technology (GMD), and a Professor of Computer Science at the University of Essen, Germany. Dr Kobsa's research lies in the areas of user modeling and personalized systems (with applications in the areas of information environments, expert finders, and user interfaces for disabled and elderly people), privacy, and in information visualization. He is the editor of User Modeling and User-Adapted Interaction, editorial board member of World-Wide Web, Universal Access in the Information Society and Information Technology and Decision Making, and was the founding president of User Modeling Inc. Dr. Kobsa edited several books and authored numerous publications in the areas of user-adaptive systems, human-computer interaction and knowledge representation. He also co-founded a national workshop series and an international conference series in these areas.
In the 1970s, AI leaders believed we would soon see all kinds of intelligent agents, agents that would easily beat grand masters at chess, speak natural language fluently and continually learn new things. These problems turned out to be much harder than they thought. Subfields formed within AI to pursue specialized research in robotics, machine vision, natural language and so on. Speech research was joined with natural language to work towards spoken language. Happily, in past 25 years, these subfields have made significant progress, to the point that there are now commercially available robots of all shapes and sizes, speech recognition engines, and vision systems taht can actually find and sometimes correctly identify faces, gaze, arms, and simple objects.
AI researchers are now putting all these pieces together, either as human-robot interaction (HRI) or, without the mechanical hardware, as on-screen agents (so called embodied conversational agents or ECAs). Building the first generation of such agents has required solving many engineering challenges, and many problems remain. In this talk, I'll give some examples of intriguing embodied intelligent agents, both the physical and on-screen types. However, to be a real success, not only must the engineering get simpler, but there must be some reason for people to want to interact with them. In this talk, I will also look at what some of these reasons might be, drawing on my own work as well as others in HRI and ECAs.
Candace Sidner is a division scientist at BAE Systems Advanced Information Technologies. She was previously a senior research scientist at Mitsubishi Electric Research Laboratories. She earned her Ph.D. at the MIT Artificial Intelligence Laboratory. Sidner is a fellow and past councilor of AAAI, as well as having served as president of the Association for Computational Linguistics, chair of the 2001 and program cochair of the 2006 International Conference on Intelligent User Interfaces, and cochair of the 2004 SIGdial Workshop on Discourse and Dialogue, and general chair of the 2007 NAACL Human Language Technology conference.
For some time, a small group of researchers has focused on using computer technology to teach humans argumentation skills, either in general or in application areas such as law, ethics, and the sciences. This research has yielded intellectual products including computational models of argumentation, techniques for integrating argumentation into human computer interfaces via argument diagrams or by engaging students in argument-making, techniques for assessing how well students learn argumentation skills, and many interesting questions. This talk surveys selected argumentation tutoring research and addresses questions about the reasons for using computers to teach argumentation, the argument features or patterns that should be represented, the utility of argumentation diagrams as teaching aids or as diagnostic tools, and how intelligent tutoring systems can adapt to teaching argumentation in ill-defined domains/tasks where there often is no one right answer. Answers to these questions have ramifications not only for the teaching of argumentation with computers but for the future direction and impact of AI research on argumentation.
Dr. Kevin Ashley holds interdisciplinary appointments as a faculty member of the Graduate Program in Intelligent Systems at the University of Pittsburgh, a Senior Scientist at the Learning Research and Development Center, a Professor of Law, and Adjunct Professor of Computer Science. His goals are to contribute to Artificial Intelligence (AI) research on case-based and analogical reasoning, argumentation and explanation and to develop instructional systems for students and professionals in case-based domains such as law and ethics. He received a B.A. in philosophy (magna cum laude) from Princeton University in 1973, J.D. (cum laude) from Harvard Law School in 1976, and Ph.D. in computer science in 1988 from the University of Massachusetts where he held an IBM Graduate Research Fellowship. He is a Fellow of the American Association for Artificial Intelligence, and a past President of the International Association of Artificial Intelligence and Law.
To build an ontology of a domain, different entities and relations must be often identified inside linguistic segments (nominal phrases, clauses, sentences, paragraphs, titles ...) by means of syntactic and semantic annotations. The Cognitive and Applicative Grammar (CAG) is a logical and linguistic model (Desclés 1990, 2004, 2005), that opens a way to bring a sound bridge between Formal Ontology, Logics, Cognitive Linguistics and Natural Language Processing. CAG is polystratal with three levels of applicative representations : (i) the first level contains the syntactical and morphological configurations of sentences and texts; Extended Categorial Grammars are formal devices used to annotate sentences in a text; (ii) the second level expresses the applicative decompositions into operators and operands with semantic interpretations of grammatical operators (abstract cases - Agent, Localizer, Instrument, Experiencer ... - , tenses and aspects, modalities, voices, ...); (iii) at the third level, the meanings of lexical operators are described in terms of "change", "movement", "control of change or movement by an agent", "intentional teleonomy whose aim is fixed", "locating an object inside a locus", "topological determinations of loci (temporal, spatial, abstract loci)"... Each unit (a dejiniendum) of a level is decomposed into a complex of more elementary units (its definiens) of an upper level; the relation between definiendum and definiens is expressed by complex formal operators, called "combinators", using the Curry's Combinatory Logic (a logic without bound variables) framework.
References : Langages applicatifs, langues naturelles et cognition, Hermés, Paris, 1990; "Combinatory Logic, Language, and Cognitive Representations", in P. Weingartner (editor), Alternative Logics. Do Sciences Need Them?, Springer, 2004, pp. 115-148; "Reasoning and Aspectual-temporal Calculus", in D. Vanderveken, Logic, Thought and Action, Springer, 2005, pp. 217-244.
Jean-Pierre Desclés is professor in Computer Sciences applied to Human Sciences at Paris-Sorbonne University. He is head of the LaLIC laboratory ("Languages, Logics, Informatics and Cognition"). He is a member of the International Academic of Philosophy of Sciences. He has published several books and articles on relations between Logics, Computer Sciences and Semantic Analysis.
Case-based reasoning is inextricably bound to memory: The storage and reuse of cases is at the heart of the CBR process. However, CBR research seldom exploits another aspect of remembering: remembering the provenance of derived information. This talk examines the value of tracking case provenance within CBR, for tasks such as guiding case-base maintenance, and also highlights opportunities for using case-based methods to leverage burgeoning activity in provenance tracking in areas such as e-science.
This talk presents joint work with Scott Dial, Joseph Morwick, and Matthew Whitehead.
David Leake is a Professor of Computer Science and the Associate Dean for Graduate Studies of the School of Informatics at Indiana University, as well as a member of the faculty of Indiana University's Cognitive Science and Human-Computer Interaction programs. He received his Ph.D. in Computer Science from Yale University in 1990. His research interests include case-based reasoning, context, explanation, human-centered computing, intelligent user interfaces, introspective reasoning, and knowledge management.
Since the first days of digital games, developers have concentrated on realistic graphical and technical effects to increase the player's awareness. Ever since games have become more and more complex until today's next generation titles, which immerse the audience into a movie-like three dimensional game world, where computer controlled characters behave almost like real humans. Development budgets for such titles easily exceed 10 to 15 million U.S. dollars. Large amounts of these budgets are spent on the innovative technologies behind the graphical effects. These efforts are intended to provide the player a realistic behaving and vivid world. Therefore, the development and implementation of several AI approaches in digital games is one of the key technologies. This talk will focus the phrase "game AI", which covers a collection of programming and design approaches that have to be adjusted for the game developers needs. Therefore the beginnings and the recent approaches regarding game AI will be depicted as a first step. Furthermore the talk will highlight a possible future fundamental change of game AI. Last but not least some possible links between game development and academia research efforts in the field of AI will be highlighted.
Florian Stadlbauer is founder and the Executive Director of the DECK13 Interactive GmbH. DECK13 is one of the leading German game studio and developer of the titles "Ankh" and "Jack Keane" which received a tremendous amount of peer and critical acclaim, including several awards from German Video Game Developer Awards 2005 and 2007. Dr. Stadlbauer studied business administration in Frankfurt and Munich and did his PhD at the Institute for Information Systems and New Media in Munich as well as at York University's Schulich School of Business in Toronto.