Samsonovich, Alexei
Mapping the Landscape of Human-Level Artificial General Intelligence
Adams, Sam (IBM) | Arel, Itmar (University of Tennessee) | Bach, Joscha (Humboldt University of Berlin) | Coop, Robert (University of Tennessee) | Furlan, Rod (Quaternix Research, Inc.) | Goertzel, Ben (Independent Researcher and Author) | Hall, J. Storrs (George Mason University) | Samsonovich, Alexei (Tufts University) | Scheutz, Matthias (Southern Illinois University, Carbondale) | Schlesinger, Matthew (University of Buffalo, State University of New York) | Shapiro, Stuart C. (VivoMind Research, LLC) | Sowa, John
Of course, this is far from the first attempt to plot a course toward human-level AGI: arguably this was the goal of the founders of the field of artificial intelligence in the 1950s, and has been pursued by a steady stream of AI researchers since, even as the majority of the AI field has focused its attention on more narrow, specific subgoals. The ideas presented here build on the ideas of others in innumerable ways, but to review the history of AI and situate the current effort in the context of its predecessors would require a much longer article than this one. Thus we have chosen to focus on the results of our AGI roadmap discussions, acknowledging in a broad way the many debts owed to many prior researchers. References to the prior literature on evaluation of advanced AI systems are given by Laird (Laird et al. 2009) and Geortzel and Bugaj (2009), which may in a limited sense be considered prequels to this article. We begin by discussing AGI in general and adopt a pragmatic goal for measuring progress toward its attainment. An initial capability landscape for AGI The heterogeneity of general intelligence in will be presented, drawing on major themes from humans makes it practically impossible to develop developmental psychology and illuminated by a comprehensive, fine-grained measurement system mathematical, physiological, and informationprocessing for AGI. While we encourage research in defining perspectives. The challenge of identifying such high-fidelity metrics for specific capabilities, appropriate tasks and environments for measuring we feel that at this stage of AGI development AGI will be taken up. Several scenarios will a pragmatic, high-level goal is the best we can be presented as milestones outlining a roadmap agree upon. I advocate beginning with a system that has minimal, although extensive, built-in capabilities. Many variant approaches have been proposed A classic example of the narrow AI approach was for achieving such a goal, and both the AI and AGI IBM's Deep Blue system (Campbell, Hoane, and communities have been working for decades on Hsu 2002), which successfully defeated world chess the myriad subgoals that would have to be champion Gary Kasparov but could not readily achieved and integrated to deliver a comprehensive apply that skill to any other problem domain without AGI system.
Reports of the AAAI 2009 Fall Symposia
Azevedo, Roger (University of Memphis) | Bench-Capon, Trevor (University of Liverpool) | Biswas, Gautam (Vanderbilt University) | Carmichael, Ted (University of North Carolina at Charlotte) | Green, Nancy (University of North Carolina at Greensboro) | Hadzikadic, Mirsad (University of North Carolina at Charlotte) | Koyejo, Oluwasanmi (University of Texas) | Kurup, Unmesh (Rensselaer Polytechnic Institute) | Parsons, Simon (Brooklyn College, City University of New York) | Pirrone, Roberto (University of Pirrone) | Prakken, Henry (Utrecht University) | Samsonovich, Alexei (George Mason University) | Scott, Donia (Open University) | Souvenir, Richard (University of North Carolina at Charlotte)
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.
Reports of the AAAI 2009 Fall Symposia
Azevedo, Roger (University of Memphis) | Bench-Capon, Trevor (University of Liverpool) | Biswas, Gautam (Vanderbilt University) | Carmichael, Ted (University of North Carolina at Charlotte) | Green, Nancy (University of North Carolina at Greensboro) | Hadzikadic, Mirsad (University of North Carolina at Charlotte) | Koyejo, Oluwasanmi (University of Texas) | Kurup, Unmesh (Rensselaer Polytechnic Institute) | Parsons, Simon (Brooklyn College, City University of New York) | Pirrone, Roberto (University of Pirrone) | Prakken, Henry (Utrecht University) | Samsonovich, Alexei (George Mason University) | Scott, Donia (Open University) | Souvenir, Richard (University of North Carolina at Charlotte)
Series, held Thursday through Saturday, November 5-7, at he Association for the Advancement of Artificial Intelligence the Westin Arlington Gateway in Arlington, Virginia. The titles of the seven symposia were as follows: (1) Biologically Inspired Cognitive Biologically Inspired Cognitive Architectures Architectures, (2) Cognitive and Metacognitive Cognitive and Metacognitive Educational Systems Educational Systems, (3) Complex Adaptive Complex Adaptive Systems and the Threshold Effect: Views from the Natural Systems and the Threshold Effect: Views and Social Sciences from the Natural and Social Sciences, (4) Manifold Manifold Learning and Its Applications Learning and Its Applications, (5) Multirepresentational Architectures for Human-Level Multirepresentational Architectures for Human-Level Intelligence Intelligence, (6) The Uses of Computational The Uses of Computational Argumentation Argumentation, and (7) Virtual Healthcare Virtual Healthcare Interaction Interaction. 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 challenge of creating a real-life computational equivalent of the human mind requires that we better understand at a computational level how natural intelligent systems develop their cognitive and learning functions. They will behave, variety of disjoined communities and schools of learn, communicate, and "think" as conscious thought that used to speak different languages and beings in general, in addition to being able to perform ignore each other.
Reports of the AAAI 2008 Fall Symposia
Beal, Jacob (BBN Technologies) | Bello, Paul A. (Office of Naval Research) | Cassimatis, Nicholas (University of Wisconsin-Madison) | Coen, Michael H. (University of Arizona) | Cohen, Paul R. (Stottler Henke) | Davis, Alex (The MITRE Corporation) | Maybury, Mark T. (George Mason University) | Samsonovich, Alexei (Rensselaer Polytechnic Institute) | Shilliday, Andrew (University of Missouri-Columbia) | Skubic, Marjorie (Rensselaer Polytechnic Institute) | Taylor, Joshua (AFRL) | Walter, Sharon (Massachusetts Institute of Technology) | Winston, Patrick (University of Massachusetts) | Woolf, Beverly Park
The Association for the Advancement of Artificial Intelligence was pleased to present the 2008 Fall Symposium Series, held Friday through Sunday, November 7-9, at the Westin Arlington Gateway in Arlington, Virginia. The titles of the seven symposia were (1) Adaptive Agents in Cultural Contexts, (2) AI in Eldercare: New Solutions to Old Problems, (3) Automated Scientific Discovery, (4) Biologically Inspired Cognitive Architectures, (5) Education Informatics: Steps toward the International Internet Classroom, (6) Multimedia Information Extraction, and (7) Naturally Inspired AI.
Reports of the AAAI 2008 Fall Symposia
Beal, Jacob (BBN Technologies) | Bello, Paul A. (Office of Naval Research) | Cassimatis, Nicholas (University of Wisconsin-Madison) | Coen, Michael H. (University of Arizona) | Cohen, Paul R. (Stottler Henke) | Davis, Alex (The MITRE Corporation) | Maybury, Mark T. (George Mason University) | Samsonovich, Alexei (Rensselaer Polytechnic Institute) | Shilliday, Andrew (University of Missouri-Columbia) | Skubic, Marjorie (Rensselaer Polytechnic Institute) | Taylor, Joshua (AFRL) | Walter, Sharon (Massachusetts Institute of Technology) | Winston, Patrick (University of Massachusetts) | Woolf, Beverly Park
These underpinnings in genetics and fields are vast, variegated, informed by memetics, studying phenomena such disparate theoretical and technical disciplines, as coalition formation in an artificial and interrelated. Other applications provided an updated perspective ethical concerns related to the use of included case-based retrieval of to a previous symposium held in fall eldercare technology to ensure that narratives culturally relevant to a 2005 on the same topic. Some models focused One major theme of the symposium The symposium ended with a more directly on adaptation, from machine-learning was to investigate the use of sensor brainstorming session on possible solutions and game-theoretic networks in the home environment to for two real-life scenarios for perspectives, but discussions suggested provide safety, to monitor activities of ailing elders and their caregivers. The ways in which those adaptations daily living, to assess physical and cognitive exercise was helpful in grounding the might vary from one cultural context function, and to identify participants in the lives of older adults to another. Work was also should address real needs.