Technology
Interactive Narrative: An Intelligent Systems Approach
Riedl, Mark Owen (Georgia Institute of Technology) | Bulitko, Vadim (University of Alberta)
Interactive narrative is a form of digital interactive experience in which users create or influence a dramatic storyline through their actions. The goal of an interactive narrative system is to immerse the user in a virtual world such that he or she believes that they are an integral part of an unfolding story and that their actions can significantly alter the direction and/or outcome of the story.In this article we review the ways in which artificial intelligence can be brought to bear on the creation of interactive narrative systems. We lay out the landscape of about 20 years of interactive narrative research and explore the successes as well as open research questions pertaining to the novel use of computational narrative intelligence in the pursuit of entertainment, education, and training.
RoboCup Rescue Robot and Simulation Leagues
Akin, H. Levent (Bogazici University) | Ito, Nobuhiro (Aichi Institute of Technology) | Jacoff, Adam (National Institute of Standards and Technology) | Kleiner, Alexander (Linköping University) | Pellenz, Johannes (V&R Vision &) | Visser, Arnoud (Robotics GmbH)
The RoboCup Rescue Robot and Simulation competitions have been held since 2000. The experience gained during these competitions has increased the maturity level of the field, which allowed deploying robots after real disasters (for example, Fukushima Daiichi nuclear disaster). This article provides an overview of these competitions and highlights the state of the art and the lessons learned.
The Eighth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment
Riedl, Mark (Georgia Institute of Technology) | Sukthankar, Gita Reese (University of Central Florida) | Jhala, Arnav (University of California, Santa Cruz) | Zhu, Jichen (Drexel University) | Villar, Santiago Ontanon (Drexel University) | Buro, Michael (University of Alberta) | Churchill, David (University of Newfoundland)
The Eighth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE) was held October 8-12, 2012, at Stanford University in Palo Alto, California. The conference included a research and industry track as well as a demonstration program. The conference featured 16 technical papers, 16 posters, and one demonstration, along with invited speakers, the StarCraft Ai competition, a newly-introduced Doctoral Consortium, and 5 workshops.
Deployed Innovative Applications of Artificial Intelligence 2012
Fromherz, Marcus (Xerox) | Muñoz-Avila, Hector (Lehigh University)
Deployed Innovative Applications of Artificial Intelligence 2012 Abstract This issue of AI Magazine features expanded versions of articles that discuss deployed applications from the 2012 AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI-12). This issue of AI Magazine features expanded versions of articles that discuss deployed applications from the 2012 AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI-12).
Applying Automated Language Translation at a Global Enterprise Level
Rychtyckyj, Nestor (Ford Motor Company) | Plesco, Craig (Ford Motor Company)
In 2007 we presented a paper that described the application of Natural Language Processing (NLP) and Machine Translation (MT) for the automated translation of process build instructions from English to other languages to support Ford's assembly plants in non-English speaking countries. This project has continued to evolve with the addition of new languages and improvements to the translation process. However, we discovered that there was a large demand for automated language translation across all of Ford Motor Company and we decided to expand the scope of our project to address these requirements. This paper will describe our efforts to meet all of Ford's internal translation requirements with AI and MT technology and focus on the challenges and lessons that we learned from applying advanced technology across an entire corporation.
A Human/Computer Learning Network to Improve Biodiversity Conservation and Research
Kelling, Steve (Cornell University) | Gerbracht, Jeff (Cornell University) | Fink, Daniel (Cornell University) | Lagoze, Carl (Cornell University) | Wong, Weng-Keen (Oregon State University) | Yu, Jun (Oregon State University) | Damoulas, Theodoros (Cornell University) | Gomes, Carla (Cornell University)
In this paper we describe eBird, a citizen-science project that takes advantage of the human observational capacity to identify birds to species, which is then used to accurately represent patterns of bird occurrences across broad spatial and temporal extents. We call this a Human-Computer Learning Network, whose core is an active learning feedback loop between humans and machines that dramatically improves the quality of both, and thereby continually improves the effectiveness of the network as a whole. In this paper we explore how Human-Computer Learning Networks can leverage the contributions of a broad recruitment of human observers and processes their contributed data with Artificial Intelligence algorithms leading to a computational power that far exceeds the sum of the individual parts.
Reports on the 2012 AAAI Fall Symposium Series
Dogan, Rezarta Islamaj (National Library of Medicine) | Gil, Yolanda (University of Southern California) | Hirsh, Haym (Rutgers University) | Krishnan, Narayanan C. (Washington State University) | Lewis, Michael (University of Pittsburgh) | Mericli, Cetin (Carnegie Mellon University) | Rashidi, Parisa (Northwestern University) | Raskin, Victor (Purdue University) | Swarup, Samarth (Virginia Institute of Technology) | Sun, Wei (George Mason University) | Taylor, Julia M. (National Library of Medicine) | Yeganova, Lana
The Association for the Advancement of Artificial Intelligence was pleased to present the 2012 Fall Symposium Series, held Friday through Sunday, November 2–4, at the Westin Arlington Gateway in Arlington, Virginia. The titles of the eight symposia were as follows: AI for Gerontechnology (FS-12-01), Artificial Intelligence of Humor (FS-12-02), Discovery Informatics: The Role of AI Research in Innovating Scientific Processes (FS-12-03), Human Control of Bio-Inspired Swarms (FS-12-04), Information Retrieval and Knowledge Discovery in Biomedical Text (FS-12-05), Machine Aggregation of Human Judgment (FS-12-06), Robots Learning Interactively from Human Teachers (FS-12-07), and Social Networks and Social Contagion (FS-12-08). The highlights of each symposium are presented in this report.
Statistical Anomaly Detection for Train Fleets
Holst, Anders (Swedish Institute of Computer Science) | Bohlin, Markus (Swedish Institute of Computer Science) | Ekman, Jan (Swedish Institute of Computer Science) | Sellin, Ola (Bombardier Transportation) | Lindström, Björn (Addiva Consulting AB) | Larsen, Stefan (Addiva Eduro AB)
We have developed a method for statistical anomaly detection which has been deployed in a tool for condition monitoring of train fleets. The anomaly detection component helps the operators to quickly find significant deviations from normal behavior and to detect early indications for possible problems. The savings in maintenance costs comes mainly from avoiding costly breakdowns, and have been estimated to several million Euros per year for the tool. In the long run, it is expected that maintenance costs can be reduced with between 5 and 10 % by using the tool.
A Real-Time Decision Support System for High Cost Oil-Well Drilling Operations
Gundersen, Odd Erik (http://www.verdandetechnology.com) | Sørmo, Frode (Verdande Technology) | Aamodt, Agnar (Norwegian Unversity of Science and Technology) | Skalle, Pål (Norwegian University of Science and Technology)
In this article we present DrillEdge -- a commercial and award winning software system that monitors oil-well drilling operations in order to reduce non-productive time (NPT). DrillEdge utilizes case-based reasoning with temporal representations on streaming real-time data, pattern matching and agent systems to predict problems and give advice on how to mitigate the problems. The methods utilized, the architecture, the GUI and development cost in addition to two case studies are documented.