SRI International
Large-Scale Analogical Reasoning
Chaudhri, Vinay K. (SRI International) | Heymans, Stijn J. (SRI International) | Overholtzer, Adam (SRI International) | Spaulding, Aaron (SRI International) | Wessel, Michael (SRI International)
Cognitive simulation of analogical processing can be used to answer comparison questions such as: What are the similarities and/or differences between A and B, for concepts A and B in a knowledge base (KB). Previous attempts to use a general-purpose analogical reasoner to answer such questions revealed three major problems: (a) the system presented too much information in the answer, and the salient similarity or difference was not highlighted; (b) analogical inference found some incorrect differences; and (c) some expected similarities were not found. The cause of these problems was primarily a lack of a well-curated KB and, and secondarily, algorithmic deficiencies. In this paper, relying on a well-curated biology KB, we present a specific implementation of comparison questions inspired by a general model of analogical reasoning. We present numerous examples of answers produced by the system and empirical data on answer quality to illustrate that we have addressed many of the problems of the previous system.
CODA: Coordinating Human Planners
Myers, Karen (SRI International) | Jarvis, Peter A. (SRI International) | Lee, Thomas D. (SRI International)
Effective coordination of distributed human planners requires timely communication of relevant information to ensure the overall coherence of activities and the compatibility of assumptions. The CODA system provides targeted information dissemination among distributed human planners as a way of improving coordination. Within CODA, each planner declares interest in different types of plan changes that could impact his or her local plan development. As individuals develop plans using a plan authoring tool, their activities are monitored; changes that match declared interests trigger automatic notification of appropriate planners. In this way, distributed planners can receive focused, real-time updates of plan changes that are relevant to their local planning efforts.
Intelligent Learning Technologies Part 2: Applications of Artificial Intelligence to Contemporary and Emerging Educational Challenges
Chaudhri, Vinay K. (SRI International) | Lane, H. Chad (University of Southern California) | Gunning, Dave (Palo Alto Research Center) | Roschelle, Jeremy (SRI International)
Part Two of the special issue of AI Magazine presents articles on some of the most interesting projects at the intersection of AI and Education. Included are articles on integrated systems such as virtual humans, an intellgent textbook a game-based learning environment as well as technology focused components such as student models and data mining. The issue concludes with an article summarizing the contemporary and emerging challenges at the intersection of AI and education.
AI Grand Challenges for Education
Woolf, Beverly Park (University of Massachusetts, Amherst) | Lane, H. Chad (University of Southern California) | Chaudhri, Vinay K. (SRI International) | Kolodner, Janet L. (Georgia Institute of Technology)
This article focuses on contributions that AI can make to address long-term educational goals. It describes five challenges that would support: (1) mentors for every learner; (2) learning twenty-first century skills; (3) interaction data to support learning; (4) universal access to global classrooms; and (5) lifelong and life-wide learning. A vision and brief research agenda are described for each challenge along with goals that lead to access to global educational resources and the reuse and sharing of digital educational resources. Instructional systems with AI technology are described that currently support richer experiences for learners and supply researchers with new opportunities to analyze vast data sets of instructional behavior from big databases, containing elements of learning, affect, motivation, and social interaction.
AI Grand Challenges for Education
Woolf, Beverly Park (University of Massachusetts, Amherst) | Lane, H. Chad (University of Southern California) | Chaudhri, Vinay K. (SRI International) | Kolodner, Janet L. (Georgia Institute of Technology)
This article focuses on contributions that AI can make to address long-term educational goals. It describes five challenges that would support: (1) mentors for every learner; (2) learning twenty-first century skills; (3) interaction data to support learning; (4) universal access to global classrooms; and (5) lifelong and life-wide learning. A vision and brief research agenda are described for each challenge along with goals that lead to access to global educational resources and the reuse and sharing of digital educational resources. Instructional systems with AI technology are described that currently support richer experiences for learners and supply researchers with new opportunities to analyze vast data sets of instructional behavior from big databases, containing elements of learning, affect, motivation, and social interaction. Personalized learning is described using computational tools that enhance student and group experience, reflection, and analysis, and supply data for development of novel theory development.
Intelligent Learning Technologies Part 2: Applications of Artificial Intelligence to Contemporary and Emerging Educational Challenges
Chaudhri, Vinay K. (SRI International) | Lane, H. Chad (University of Southern California) | Gunning, Dave (Palo Alto Research Center) | Roschelle, Jeremy (SRI International)
Part Two of the special issue of AI Magazine presents articles on some of the most interesting projects at the intersection of AI and Education. Included are articles on integrated systems such as virtual humans, an intellgent textbook a game-based learning environment as well as technology focused components such as student models and data mining. The issue concludes with an article summarizing the contemporary and emerging challenges at the intersection of AI and education.
Invited Talks
Doyle, Richard J. (NASA Jet Propulsion Laboratory) | Dumontier, Michel (Stanford University) | Hirsh, Haym (Cornell University) | Jensen, David (University of Massachusetts at Amherst) | Karp, Peter (SRI International) | Monteleoni, Claire (George Washington University) | Obradovic, Zoen (Temple University) | Re, Christopher (Stanford University) | Rzhetsky, Andrey (University of Chicago) | Wagstaff, Kiri L. (NASA Jet Propulsion Laboratory)
Abstracts of the invited talks presented at the AAAI Fall Symposium on Discovery Informatics: AI Takes a Science-Centered View on Big Data. Talks include A Data Lifecycle Approach to Discovery Informatics, Generating Biomedical Hypotheses Using Semantic Web Technologies, Socially Intelligent Science, Representing and Reasoning with Experimental and Quasi-Experimental Designs, Bioinformatics Computation of Metabolic Models from Sequenced Genomes, Climate Informatics: Recent Advances and Challenge Problems for Machine Learning in Climate Science, Predictive Modeling of Patient State and Therapy Optimization, Case Studies in Data-Driven Systems: Building Carbon Maps to Finding Neutrinos, Computational Analysis of Complex Human Disorders, and Look at This Gem: Automated Data Prioritization for Scientific Discovery of Exoplanets, Mineral Deposits, and More.
Inquire Biology: A Textbook that Answers Questions
Chaudhri, Vinay K. (SRI International) | Cheng, Britte (SRI International) | Overtholtzer, Adam (SRI International) | Roschelle, Jeremy (SRI International) | Spaulding, Aaron (SRI International) | Clark, Peter (Vulcan Inc.) | Greaves, Mark (Pacific Northwest National Laboratory) | Gunning, Dave (Palo Alto Research Center)
Inquire Biology is a prototype of a new kind of intelligent textbook -- one that answers students' questions, engages their interest, and improves their understanding. Inquire Biology provides unique capabilities via a knowledge representation that captures conceptual knowledge from the textbook and uses inference procedures to answer students' questions. In an initial controlled experiment, community college students using the Inquire Biology prototype outperformed students using either a hardcopy or conventional E-book version of the same biology textbook. While additional research is needed to fully develop Inquire Biology, the initial prototype clearly demonstrates the promise of applying knowledge representation and question-answering technology to electronic textbooks.
Intelligent Learning Technologies: Applications of Artificial Intelligence to Contemporary and Emerging Educational Challenges
Chaudhri, Vinay K. (SRI International) | Lane, H. Chad (University of Southern California) | Gunning, Dave (Palo Alto Research Center) | Roschelle, Jeremy (SRI International)
This special issue of AI Magazine presents articles on some of the most interesting projects at the intersection of AI and Education. Included are articles on integrated systems such as virtual humans, an intellgent textbook a game-based learning environment as well as technology focused components such as student models and data mining. The issue concludes with an article summarizing the contemporary and emerging challenges at the intersection of AI and education.
Intelligent Learning Technologies: Applications of Artificial Intelligence to Contemporary and Emerging Educational Challenges
Chaudhri, Vinay K. (SRI International) | Lane, H. Chad (University of Southern California) | Gunning, Dave (Palo Alto Research Center) | Roschelle, Jeremy (SRI International)
This special issue of AI Magazine presents articles on some of the most interesting projects at the intersection of AI and Education. Included are articles on integrated systems such as virtual humans, an intellgent textbook a game-based learning environment as well as technology focused components such as student models and data mining. The issue concludes with an article summarizing the contemporary and emerging challenges at the intersection of AI and education.