If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Blisard, Sam (Naval Research Laboratory) | Carmichael, Ted (University of North Carolina at Charlotte) | Ding, Li (University of Maryland, Baltimore County) | Finin, Tim (University of Maryland, Baltimore County) | Frost, Wende (Naval Research Laboratory) | Graesser, Arthur (University of Memphis) | Hadzikadic, Mirsad (University of North Carolina at Charlotte) | Kagal, Lalana (Massachusetts Institute of Technology) | Kruijff, Geert-Jan M. (German Research Center for Artificial Intelligence) | Langley, Pat (Arizona State University) | Lester, James (North Carolina State University) | McGuinness, Deborah L. (Rensselaer Polytechnic Institute) | Mostow, Jack (Carnegie Mellon University) | Papadakis, Panagiotis (University of Sapienza, Rome) | Pirri, Fiora (Sapienza University of Rome) | Prasad, Rashmi (University of Wisconsin-Milwaukee) | Stoyanchev, Svetlana (Columbia University) | Varakantham, Pradeep (Singapore Management University)
The Association for the Advancement of Artificial Intelligence was pleased to present the 2011 Fall Symposium Series, held Friday through Sunday, November 4–6, at the Westin Arlington Gateway in Arlington, Virginia. The titles of the seven symposia are as follows: (1) Advances in Cognitive Systems; (2) Building Representations of Common Ground with Intelligent Agents; (3) Complex Adaptive Systems: Energy, Information and Intelligence; (4) Multiagent Coordination under Uncertainty; (5) Open Government Knowledge: AI Opportunities and Challenges; (6) Question Generation; and (7) Robot-Human Teamwork in Dynamic Adverse Environment. The highlights of each symposium are presented in this report.
Barkowsky, Thomas (University of Bremen) | Bertel, Sven (University of Illinois at Urbana-Champaign) | Broz, Frank (University of Hertfordshire) | Chaudhri, Vinay K. (SRI International) | Eagle, Nathan (txteagle, Inc.) | Genesereth, Michael (Stanford University) | Halpin, Harry (University of Edinburgh) | Hamner, Emily (Carnegie Mellon University) | Hoffmann, Gabe (Palo Alto Research Center) | Hölscher, Christoph (University of Freiburg) | Horvitz, Eric (Microsoft Research) | Lauwers, Tom (Carnegie Mellon University) | McGuinness, Deborah L. (Rensselaer Polytechnic Institute) | Michalowski, Marek (BeatBots LLC) | Mower, Emily (University of Southern California) | Shipley, Thomas F. (Temple University) | Stubbs, Kristen (iRobot) | Vogl, Roland (Stanford University) | Williams, Mary-Anne (University of Technology)
The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, is pleased to present the 2010 Spring Symposium Series, to be held Monday through Wednesday, March 22–24, 2010 at Stanford University. The titles of the seven symposia are Artificial Intelligence for Development; Cognitive Shape Processing; Educational Robotics and Beyond: Design and Evaluation; Embedded Reasoning: Intelligence in Embedded Systems Intelligent Information Privacy Management; It's All in the Timing: Representing and Reasoning about Time in Interactive Behavior; and Linked Data Meets Artificial Intelligence.
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.
We describe an intelligent personal assistant that has been developed to aid a busy knowledge worker in managing time commitments and performing tasks. The design of the system was motivated by the complementary objectives of (1) relieving the user of routine tasks, thus allowing her to focus on tasks that critically require human problem-solving skills, and (2) intervening in situations where cognitive overload leads to oversights or mistakes by the user. The system draws on a diverse set of AI technologies that are linked within a Belief-Desire-Intention (BDI) agent system. Although the system provides a number of automated functions, the overall framework is highly user centric in its support for human needs, responsiveness to human inputs, and adaptivity to user working style and preferences.
Aliod, Diego Molla, Alonso, Eduardo, Bangalore, Srinivas, Beck, Joseph, Bhanu, Bir, Blythe, Jim, Boddy, Mark, Cesta, Amedeo, Grobelink, Marko, Hakkani-Tur, Dilek, Harabagiu, Sanda, Lege, Alain, McGuinness, Deborah L., Marsella, Stacy, Milic-Frayling, Natasha, Mladenic, Dunja, Oblinger, Dan, Rybski, Paul, Shvaiko, Pavel, Smith, Stephen, Srivastava, Biplav, Tejada, Sheila, Vilhjalmsson, Hannes, Thorisson, Kristinn, Tur, Gokhan, Vicedo, Jose Luis, Wache, Holger
The AAAI-05 workshops were held on Saturday and Sunday, July 9-10, in Pittsburgh, Pennsylvania. The thirteen workshops were Contexts and Ontologies: Theory, Practice and Applications, Educational Data Mining, Exploring Planning and Scheduling for Web Services, Grid and Autonomic Computing, Human Comprehensible Machine Learning, Inference for Textual Question Answering, Integrating Planning into Scheduling, Learning in Computer Vision, Link Analysis, Mobile Robot Workshop, Modular Construction of Humanlike Intelligence, Multiagent Learning, Question Answering in Restricted Domains, and Spoken Language Understanding.
TheGeneral Motors Variation-Reduction Adviser is a knowledge system built on case-based reasoning principles that is currently in use in eighteen General Motors asssembly centers. This article reviews the overall characteristics of the system and then focuses on various AI elements critical to support its deployment to a production system. A key AI enabler is ontology-guided search using domainspecific ontologies.