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.
We present an innovative approach for large-scale data collection in human-robot interaction research through the use of online multi-player games. By casting a robotic task as a collaborative game, we gather thousands of examples of human-human interactions online, and then leverage this corpus of action and dialog data to create contextually relevant, social and task-oriented behaviors for human-robot interaction in the real world. We demonstrate our work in a collaborative search and retrieval task requiring dialog, action synchronization and action sequencing between the human and robot partners. A user study performed at the Boston Museum of Science shows that the autonomous robot exhibits many of the same patterns of behavior that were observed in the online dataset and survey results rate the robot similarly to human partners in several critical measures.
CMRoboBits is a course offered at Carnegie Mellon University that introduces students to all the concepts needed to create a complete intelligent robot. In particular, the course focuses on the areas of perception, cognition, and action by using the Sony AIBO robot as the focus for the programming assignments. This course shows how an AIBO and its software resources make it possible for students to investigate and work with an unusually broad variety of AI topics within a single semester. While material presented in this article describes using AIBOs as the primary platform, the concepts presented in the course are not unique to the AIBO and can be applied on different kinds of robotic hardware.