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) …
The Fourth Symposium on Abstraction, Reformulation, and Approximation (SARA) took place at Horseshoe Bay Resort and Conference Club, Lake LBJ, Texas, from 26 to 29 July 2000, just prior to the Seventeenth National Conference on Artificial Intelligence (AAAI-2000) conference in Austin. Previous SARA conferences were held at Jackson Hole in Wyoming (1994); Ville d'Esterel in Quebec (1995); and Asilomar in Monterey, California (1998). The symposium grew out of a series of workshops on abstraction and approximation and on reformulation that had taken place alongside the American Association for Artificial Intelligence (AAAI) conference since 1989. SARA is a meeting with an unusually broad subject area. From the earliest days of AI, abstractions and problem reformulations and approximations have been recognized as central to AI for reasoning effectively in complex domains.
This symposium was motivated by the recognition that even as autonomous system technologies mature into practical applications, humans still refuse to disappear. Humans stay in the loop, so practical applications require that the autonomous software be understandable and adjustable. Adjustable autonomy means dynamically adjusting the level of autonomy of an agent depending on the situation. For real-world teaming between humans and autonomous agents, the desired or optimal level of control can vary over time. Hence, effective autonomous agents will support adjustable autonomy, which contrasts with most work in autonomous systems, where the style of interaction between the human and the agent are fixed by design. The adjustable autonomy concept includes the ability for humans to adjust the autonomy of agents, for agents to adjust their own autonomy, and for a group of agents to adjust the autonomy relationships within the group.
The American Association for Artificial Intelligence held its 1996 Spring Symposia Series on March 27 to 29 at Stanford University. This article contains summaries of the eight symposia that were conducted: (1) Acquisition, Learning, and Demonstration: Automating Tasks for Users; (2) Adaptation, Coevolution, and Learning in Multiagent Systems; (3) Artificial Intelligence in Medicine: Applications of Current Technologies; (4) Cognitive and Computational Models of Spatial Representation; (5) Computational Implicature: Computational Approaches to Interpreting and Generating Conversational Implicature; (6) Computational Issues in Learning Models of Dynamic Systems; (7) Machine Learning in Information Access; and (8) Planning with Incomplete Information for Robot Problems. This article contains summaries of the eight symposia that were conducted: (1) Acquisition, Learning, and Demonstration: Automating Tasks for Users; (2) Adaptation, Coevolution, and Learning in Multiagent Systems; (3) Artificial Intelligence in Medicine: Applications of Current Technologies; (4) Cognitive and Computational Models of Spatial Representation; (5) Computational Implicature: Computational Approaches to Interpreting and Generating Conversational Implicature; (6) Computational Issues in Learning Models of Dynamic Systems; (7) Machine Learning in Information Access; and (8) Planning with Incomplete Information for Robot Problems. This symposium brought together three different communities that are all looking at the problem of automating tasks through interactions with users: First, knowledge acquisition concentrates on how to structure a system's interactions with users based on the nature of the task to be automated. Second, machine learning seeks automated algorithms that do explanation or induction based on a user's actions.
This symposium reexamined the view (proposed by Austin and developed by Searle and others) of communication as action rather than transmission of information. Such a view has become popular as a characterization of language use, and it plays a central role in the dialogue-management components of many systems that communicate with human users or other agents. An abstract level of representation such as speech acts is also useful as a media-independent characterization of the function of communication. Current work that was presented and discussed at the symposium included both extensions to classical speech-act theory as well as attempts at standardization of speech-act labels. The extensions included accounts of dialogue phenomena other than classical illocutionary acts, such as turn taking, feedback, problem solving, and persuasion as well as the importance of social phenomena such as rights, roles, and obligations.
The titles of the five symposia were Modal and Temporal Logics-Based Planning for Open Networked Multimedia Systems Narrative Intelligence Psychological Models of Communication in Collaborative Systems Question-Answering Systems Using Layout for the Generation, Understanding, or Retrieval of Documents This article concludes with a previously unpublished report on the 1998 AAAI Fall Symposium on AI and Link Analysis. This symposium provided a forum for researchers involved in using formal methods and in design of networked multimedia systems and adaptivereactive systems to identify common ground, relevant experiences, applications, open problems, and possible future developments. To support intelligent and interactive multimedia applications, there's a need to tailor systems to possess and use knowledge about the application domain, user-requirement tasks, the context of interaction, communication, and performance parameters. Temporal and modal logics have been used to reason about time, action, and adaptive change and to program and verify networked systems. The 1999 American Association for Artificial Intelligence Fall Symposium Series was held Friday through Sunday, 5-7 November 1999, at the Sea Crest Oceanfront Resort and Conference Center.
Several successful researchers discussed what they believed made them successful, and provided advice on how to play the funding game. The American Association for Artificial Intelligence presented its 2004 Fall Symposium Series Friday through Sunday, October 22-24 at the Hyatt Regency Crystal City in Arlington, Virginia, adjacent to Washington, DC. The symposium series was preceded by a one-day AI funding seminar. The topics of the eight symposia in the 2004 Fall Symposia Series were: (1) Achieving Human-Level Intelligence through Integrated Systems and Research; (2) Artificial Multiagent Learning; (3) Compositional Connectionism in Cognitive Science; (4) Dialogue Systems for Health Communications; (5) The Intersection of Cognitive Science and Robotics: From Interfaces to Intelligence; (6) Making Pen-Based Interaction Intelligent and Natural; (7) Real-Life Reinforcement Learning; and (8) Style and Meaning in Language, Art, Music, and Design. The symposium series was preceded on Thursday, October 21 by a one-day AI funding seminar, which was open to all registered attendees.
The Association for the Advancement of Artificial Intelligence was pleased to present the 2009 Fall Symposium Series, held Thursday through Saturday, November 5-7, at the Westin Arlington Gateway in Arlington, Virginia. The Symposium Series was preceded on Wednesday, November 4, by a one-day AI funding seminar. The titles of the seven symposia were as follows: (1) Biologically Inspired Cognitive Architectures, (2) Cognitive and Metacognitive Educational Systems, (3) Complex Adaptive Systems and the Threshold Effect: Views from the Natural and Social Sciences, (4) Manifold Learning and Its Applications, (5) Multirepresentational Architectures for Human-Level Intelligence, (6) The Uses of Computational Argumentation, and (7) Virtual Healthcare Interaction. The Symposium Series was preceded on Wednesday, November 4, by a one-day AI funding seminar. An informal reception was held on Thursday, November 5. A general plenary session, in which the highlights of each symposium were presented, was held on Friday, November 6.
The American Association for Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, presented the 2004 Spring Symposium Series, Monday through Wednesday, March 22-24, at Stanford University. The titles of the eight symposia were (1) Accessible Hands-on Artificial Intelligence and Robotics Education; (2) Architectures for Modeling Emotion: Cross-Disciplinary Foundations; (3) Bridging the Multiagent and Multirobotic Research Gap; (4) Exploring Attitude and Affect in Text: Theories and Applications; (5) Interaction between Humans and Autonomous Systems over Extended Operation; (6) Knowledge Representation and Ontologies for Autonomous Systems; (7) Language Learning: An Interdisciplinary Perspective; and (8) Semantic Web Services. Each symposium had limited attendance. Most symposia chairs elected to create AAAI technical reports of their symposium, which are available as paperbound reports or (for AAAI members) are downloadable on the AAAI members-only Web site. This report includes summaries of the eight symposia, written by the symposia chairs.
The six symposia held were AI, the Fundamental Social Aggregation Challenge (cochaired by W. F. Lawless, Don Sofge, Mark Klein, and Laurent Chaudron); Designing Intelligent Robots (cochaired by George Konidaris, Byron Boots, Stephen Hart, Todd Hester, Sarah Osentoski, and David Wingate); Game Theory for Security, Sustainability, and Health (cochaired by Bo An and Manish Jain); Intelligent Web Services Meet Social Computing (cochaired by Tomas Vitvar, Harith Alani, and David Martin); Self-Tracking and Collective Intelligence for Personal Wellness (cochaired by Takashi Kido and Keiki Takadama); and Wisdom of the Crowd (cochaired by Caroline Pantofaru, Sonia Chernova, and Alex Sorokin). The papers of the six symposia were published in the AAAI technical report series. The focus of the AI, The Fundamental Social Aggregation Challenge, and the Autonomy of Hybrid Agent Groups symposium was to explore issues associated with the control of teams of humans, autonomous machines, and robots working together as hybrid agent groups. Bill Lawless of Paine College kicked off the meeting by pointing out the need for a new theory of social dynamics. He showed that majority rule is far better than consensus for group decision processes and proposed a new mathematical model for characterizing social group dynamics based on interdependence.
The titles of the eight symposia were Analyzing Microtext; Creativity and (Early) Cognitive Development; Data-Driven Wellness: From Self-Tracking to Behavior Change; Designing Intelligent Robots: Reintegrating AI II; Lifelong Machine Learning; Shikakeology: Designing Triggers for Behavior Change; Trust and Autonomous Systems; and Weakly Supervised Learning from Multimedia. This report contains summaries of the symposia, written, in most cases, by the cochairs of the symposium. Much progress has been made in recent years in several areas within natural language processing. However, so far there has been less work related to microtext (for example, instant messaging, transcribed speech, and microblogs such as Twitter and Facebook). Microtext is made up of semistructured pieces of text that are distinguished by their brevity, informality, idiosyncratic lexicon, nonstandard grammar, misspelling, use of emoticons, and sometimes simultaneous interwoven conversation.