AAAI 2008 Spring Symposia Reports
Balduccini, Marcello (Eastman Kodak Company) | Baral, Chitta (Arizona State University) | Brodaric, Boyan (Geological Survey of Canada) | Colton, Simon (Imperial College, London) | Fox, Peter (National Center for Atmospheric Research) | Gutelius, David (SRI International) | Hinkelmann, Knut (University of Applied Sciences Northwestern Switzerland) | Horswill, Ian (Northwestern University) | Huberman, Bernardo (HP Labs) | Hudlicka, Eva (Psychometrix Associates) | Lerman, Kristina (USC Information Sciences Institute) | Lisetti, Christine (Florida International University) | McGuinness, Deborah L. (Rensselaer Polytechnic Institute) | Maher, Mary Lou (National Science Foundation) | Musen, Mark A. (Stanford University) | Sahami, Mehran (Stanford University) | Sleeman, Derek (University of Aberdeen) | Thönssen, Barbara (University of Applied Sciences Northwestern Switzerland) | Velasquez, Juan D. (MIT CSAIL) | Ventura, Dan (Brigham Young University)
The titles of the eight symposia were as follows: (1) AI Meets Business Rules and Process Management, (2) Architectures for Intelligent Theory-Based Agents, (3) Creative Intelligent Systems, (4) Emotion, Personality, and Social Behavior, (5) Semantic Scientific Knowledge Integration, (6) Social Information Processing, (7) Symbiotic Relationships between Semantic Web and Knowledge Engineering, (8) Using AI to Motivate Greater Participation in Computer Science The goal of the AI Meets Business Rules and Process Management AAAI symposium was to investigate the various approaches and standards to represent business rules, business process management and the semantic web with respect to expressiveness and reasoning capabilities. The Semantic Scientific Knowledge Symposium was interested in bringing together the semantic technologies community with the scientific information technology community in an effort to build the general semantic science information community. The Social Information Processing's goal was to investigate computational and analytic approaches that will enable users to harness the efforts of large numbers of other users to solve a variety of information processing problems, from discovering high-quality content to managing common resources. The purpose of the Using AI to Motivate Greater Participation in Computer Science symposium was to identify ways that topics in AI may be used to motivate greater student participation in computer science by highlighting fun, engaging, and intellectually challenging developments in AI-related curriculum at a number of educational levels.
Sep-15-2008