Agarwal, Nitin (University of Arkansas at Little Rock) | Andrist, Sean (University of Wisconsin-Madison) | Bohus, Dan (Microsoft Research) | Fang, Fei (University of Southern California) | Fenstermacher, Laurie (Wright-Patterson Air Force Base) | Kagal, Lalana (Massachusetts Institute of Technology) | Kido, Takashi (Rikengenesis) | Kiekintveld, Christopher (University of Texas at El Paso) | Lawless, W. F. (Paine College) | Liu, Huan (Arizona State University) | McCallum, Andrew (University of Massachusetts) | Purohit, Hemant (Wright State University) | Seneviratne, Oshani (Massachusetts Institute of Technology) | Takadama, Keiki (University of Electro-Communications) | Taylor, Gavin (US Naval Academy)
The AAAI 2015 Spring Symposium Series was held Monday through Wednesday, March 23-25, at Stanford University near Palo Alto, California. The titles of the seven symposia were Ambient Intelligence for Health and Cognitive Enhancement, Applied Computational Game Theory, Foundations of Autonomy and Its (Cyber) Threats: From Individuals to Interdependence, Knowledge Representation and Reasoning: Integrating Symbolic and Neural Approaches, Logical Formalizations of Commonsense Reasoning, Socio-Technical Behavior Mining: From Data to Decisions, Structured Data for Humanitarian Technologies: Perfect Fit or Overkill? and Turn-Taking and Coordination in Human-Machine Interaction.The highlights of each symposium are presented in this report.
In 2009 we presented the idea of using collaborative filtering within a complex software application to help users learn new and relevant commands (Matejka et al. 2009). This project continued to evolve and we explored the design space of a contextual software command recommender system and completed a six-week user study (Li et al. 2011). We then expanded the scope of our project by implementing CommunityCommands, a fully functional and deployable recommender system. CommunityCommands was a publically available plug-in for Autodesk’s flagship software application AutoCAD. During a one-year period, the recommender system was used by more than 1100 users. In this article, we discuss how our practical system architecture was designed to leverage Autodesk’s existing Customer Involvement Program (CIP) data to deliver in-product contextual recommendations to end-users. We also present our system usage data and payoff, and provide an in-depth discussion of the challenges and design issues associated with developing and deploying the software command recommender system. Our work sets important groundwork for the future development of recommender systems within the domain of end-user software learning assistance.
Cohen, Adam B. (Independent Consultant) | Chernova, Sonia (Worcester Polytechnic Institute) | Giordano, James (Georgetown University Medical Center) | Guerin, Frank (University of Aberdeen) | Hauser, Kris (Duke University) | Indurkhya, Bipin (AGH University of Science and Technology) | Leonetti, Matteo (University of Texas at Austin) | Medsker, Larry (Siena College) | Michalowski, Martin (Adventium Labs) | Sonntag, Daniel (German Research Center for Artificial Intelligence) | Stojanov, Georgi (American University of Paris) | Tecuci, Dan G. (IBM Watson, Austin) | Thomaz, Andrea (Georgia Institute of Technology) | Veale, Tony (University College Dublin) | Waltinger, Ulli (Siemens Corporate Technology)
The AAAI 2014 Fall Symposium Series was held Thursday through Saturday, November 13–15, at the Westin Arlington Gateway in Arlington, Virginia adjacent to Washington, DC. The titles of the seven symposia were Artificial Intelligence for Human-Robot Interaction, Energy Market Prediction, Expanding the Boundaries of Health Informatics Using AI, Knowledge, Skill, and Behavior Transfer in Autonomous Robots, Modeling Changing Perspectives: Reconceptualizing Sensorimotor Experiences, Natural Language Access to Big Data, and The Nature of Humans and Machines: A Multidisciplinary Discourse. The highlights of each symposium are presented in this report.
Davis, Randall (Massachusetts Institute of Technology) | Libon, David (Drexel University College of Medicine) | Au, Roda (Boston University School of Medicine) | Pitman, David (Kytheram) | Penney, Dana (Lahey Hospital and Medical Center)
The digital clock drawing test is a fielded application that provides a major advance over existing neuropsychological testing technology. It captures and analyzes high precision information about both outcome and process, opening up the possibility of detecting subtle cognitive impairment even when test results appear superficially normal. We describe the design and development of the test, document the role of AI in its capabilities, and report on its use over the past seven years. We outline its potential implications for earlier detection and treatment of neurological disorders. We set the work in the larger context of the THink project, which is exploring multiple approaches to determining cognitive status through the detection and analysis of subtle behaviors.
Wobcke, Wayne (University of New South Wales) | Krzywicki, Alfred (University of New South Wales) | Kim, Yang Sok (Keimyung University) | Cai, Xiongcai (University of New South Wales) | Bain, Michael (University of New South Wales) | Compton, Paul (University of New South Wales) | Mahidadia, Ashesh (smartAcademic)
Online dating is a prime application area for recommender systems, as users face an abundance of choice, must act on limited information, and are participating in a competitive matching market. This article reports on the successful deployment of a people-to-people recommender system on a large commercial online dating site. The deployment was the result of thorough evaluation and an online trial of a number of methods, including profile-based, collaborative filtering and hybrid algorithms. Results taken a few months after deployment show that the recommender system delivered its projected benefits.
Vallati, Mauro (University of Huddersfield) | Chrpa, Lukas (University of Huddersfield) | Grześ, Marek (University of Kent) | McCluskey, Thomas Leo (University of Huddersfield) | Roberts, Mark (Naval Research Laboratory) | Sanner, Scott (NICTA) | Editor, Managing (AAAI)
We review the 2014 International Planning Competition (IPC-2014), the eighth in a series of competitions starting in 1998. IPC-2014 was held in three separate parts to assess state-of-the-art in three prominent areas of planning research: the deterministic (classical) part (IPCD), the learning part (IPCL), and the probabilistic part (IPPC). Each part evaluated planning systems in ways that pushed the edge of existing planner performance by introducing new challenges, novel tasks, or both. The competition surpassed again the number of competitors than its predecessor, highlighting the competition’s central role in shaping the landscape of ongoing developments in evaluating planning systems.
This issue features expanded versions of articles selected from the 2014 AAAI Conference on Innovative Applications of Artificial Intelligence held in Quebec City, Canada. We present a selection of four articles describing deployed applications plus two more articles that discuss work on emerging applications.
Yeh, Peter Z. (Nuance Communications) | Ramachandran, Deepak (Nuance Communications) | Douglas, Benjamin (Nuance Communications) | Ratnaparkhi, Adwait (Nuance Communications) | Jarrold, William (Nuance Communications) | Provine, Ronald (Nuance Communications) | Patel-Schneider, Peter F. (Nuance Communications) | Laverty, Stephen (Nuance Communications) | Tikku, Nirvana (Nuance Communications) | Brown, Sean (Nuance Communications) | Mendel, Jeremy (Nuance Communications) | Emfield, Adam (Nuance Communications)
In this article, we report on a multiphase R&D effort to develop a conversational second screen application for TV program discovery. Our goal is to share with the community the breadth of artificial intelligence (AI) and natural language (NL) technologies required to develop such an application along with learnings from target end-users. We first give an overview of our application from the perspective of the end-user. We then present the architecture of our application along with the main AI and NL components, which were developed over multiple phases. The first phase focuses on enabling core functionality such as effectively finding programs matching the user’s intent. The second phase focuses on enabling dialog with the user. Finally, we present two user studies, corresponding to these two phases. The results from both studies demonstrate the effectiveness of our application in the target domain.