SPE
Reports on the 2013 AAAI Fall Symposium Series
Burns, Gully (Information Sciences Institute, University of Southern California) | Gil, Yolanda (Information Sciences Institute and Department of Computer Science, University of Southern California) | Liu, Yan (University of Southern California) | Villanueva-Rosales, Natalia (University of Texas at El Paso) | Risi, Sebastian (University of Copenhagen) | Lehman, Joel (University of Texas at Austin) | Clune, Jeff (University of Wyoming) | Lebiere, Christian (Carnegie Mellon University) | Rosenbloom, Paul S. (University of Southern California) | Harmelen, Frank van (Vrije Universiteit Amsterdam) | Hendler, James A. (Rensselaer Polytechnic Institute) | Hitzler, Pascal (Wright State University) | Janowic, Krzysztof (University of California, Santa Barbara) | Swarup, Samarth (Virginia Polytechnic Institute and State University)
The Association for the Advancement of Artificial Intelligence was pleased to present the 2013 Fall Symposium Series, held Friday through Sunday, November 15–17, at the Westin Arlington Gateway in Arlington, Virginia near Washington DC USA. The titles of the five symposia were as follows: Discovery Informatics: AI Takes a Science-Centered View on Big Data (FS-13-01); How Should Intelligence be Abstracted in AI Research: MDPs, Symbolic Representations, Artificial Neural Networks, or --? The highlights of each symposium are presented in this report.
Sequential Decision Making in Computational Sustainability via Adaptive Submodularity
Krause, Andreas (ETH Zurich) | Golovin, Daniel (Google) | Converse, Sarah (USGS Patuxent Wildlife Research Center)
Many problems in computational sustainability require making a sequence of decisions in complex, uncertain environments. In this article, we review the recently discovered notion of adaptive submodularity, an intuitive diminishing returns condition that generalizes the classical notion of submodular set functions to sequential decision problems. We illustrate this concept in several case studies of interest in computational sustainability: First, we demonstrate how it can be used to efficiently plan for resolving uncertainty in adaptive management scenarios. Secondly, we show how it applies to dynamic conservation planning for protecting endangered species, a case study carried out in collaboration with the US Geological Survey and the US Fish and Wildlife Service.
The Ninth Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE): A Report
Sukthankar, Gita (University of Central Florida) | Horswill, Ian (Northwestern University)
The Ninth Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE) was held October 14–18, 2013, at Northeastern University in Boston, Massachusetts. The mission of the AIIDE conference is to provide a forum for researchers and game developers to discuss ways that AI can enhance games and other forms of interactive entertainment. In addition to presentations on adapting standard AI techniques such as search, planning and machine learning for use within games, key topic areas include creating realistic autonomous characters, interactive narrative, procedural content generation, and integrating AI into game design and production tools.
ICAIL 2013: The Fourteenth International Conference on Artificial Intelligence and Law
Verheij, Bart (University of Groningen) | Francesconi, Enrico (Institute of Legal Information Theory and Techniques - ITTIG-CNR) | Gardner, Anne (Independent research professional)
ICAIL 2013: The Fourteenth International Conference on Artificial Intelligence and Law Abstract The 14th International Conference on AI and Law (ICAIL 2013) was held in Rome, Italy, June 10-14, 2013. The 14th International Conference on AI and Law (ICAIL 2013) was held in Rome, Italy, June 10-14, 2013.
Active Learning in Lecture with Peer Instruction
Lee, Cynthia Bailey (Stanford University)
Have you ever been surprised by poor class performance on a midterm question, and wondered why you were met with silence each time you asked "Any questions?" during the lecture on that topic? Do your students sometimes feel like they understood everything that was said in lecture, only to go home, start the homework, and immediately get stuck? Do you find that you only really learn something when you have to explain it to others?
Workshops Held at the Ninth Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE): A Report
Liapis, Antonios (Technical University of Copenhagen) | Cook, Michael (Goldsmiths College London) | Smith, Adam M. (University of Washington) | Smith, Gillian (Northeastern University) | Zook, Alexander (Georgia Institute of Technology) | Si, Mei (Rensselaer Polytechnic Institute) | Cavazza, Marc (Teesside University) | Pasquier, Philippe (Simon Fraser University)
The Ninth Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE) was held October 14–18, 2013, at Northeastern University in Boston, Massachusetts. Workshops were held on the two days prior to the start of the main conference, giving attendees a chance to hold in-depth discussions on topics that complement the themes of the main conference program. This year the workshops included the First Workshop on AI and Game Aesthetics (1 day), The Second Workshop on AI in the Game Design Process (1 day), The Second International Workshop on Musical Metacreation (2 day), The Sixth Workshop on Intelligent Narrative Technologies (2 day).
The MiniZinc Challenge 2008–2013
Stuckey, Peter J. (National ICT Australia and the University of Melbourne) | Feydy, Thibaut (National ICT Australia and the University of Melbourne) | Schutt, Andreas (National ICT Australia and the University of Melbourne) | Tack, Guido (National ICT Australia and Monash University) | Fischer, Julien (Opturion)
MiniZinc is a solver agnostic modeling language for defining and solver combinatorial satisfaction and optimization problems. MiniZinc provides a solver independent modeling language which is now supported by constraint programming solvers, mixed integer programming solvers, SAT and SAT modulo theory solvers, and hybrid solvers. Since 2008 we have run the MiniZinc challenge every year, which compares and contrasts the different strengths of different solvers and solving technologies on a set of MiniZinc models. Here we report on what we have learnt from running the competition for 6 years.
A Constraint-Based Dental School Timetabling System
Cambazard, Hadrien (Université de Grenoble) | O'Sullivan, Barry (University College Cork) | Simonis, Helmut (University College Cork)
We describe a constraint-based timetabling system that was developed for the dental school based at Cork University Hospital in Ireland. Dental school timetabling differs from other university course scheduling in that certain clinic sessions can be used by multiple courses at the same time, provided a limit on room capacity is satisfied. Solutions for the years 2010, 2011 and 2012 have been used in the dental school, replacing a manual timetabling process, which could no longer cope with increasing student numbers and resulting resource bottlenecks. The use of the automated system allowed the dental school to increase the number of students enrolled to the maximum possible given the available resources.
Natural Language Access to Enterprise Data
Waltinger, Ulli (Siemens AG) | Tecuci, Dan (Siemens Corporation) | Olteanu, Mihaela (Siemens AG) | Mocanu, Vlad (Siemens AG) | Sullivan, Sean (Siemens Energy Inc.)
This paper describes USI Answers -- a natural language question answering system for enterprise data. We report on the progress towards the goal of offering easy access to enterprise data to a large number of business users, most of whom are not familiar with the specific syntax or semantics of the underlying data sources. Additional complications come from the nature of the data, which comes both as structured and unstructured. The proposed solution allows users to express questions in natural language, makes apparent the system's interpretation of the query, and allows easy query adjustment and reformulation.
Using Analogy to Cluster Hand-Drawn Sketches for Sketch-Based Educational Software
Chang, Maria D. (Northwestern University) | Forbus, Kenneth D. (Northwestern University)
Useful feedback makes use of models of domain-specific knowledge, especially models that are commonly held by potential students. To empirically determine what these models are, student data can be clustered to reveal common misconceptions or common problem-solving strategies. We use this approach to cluster a corpus of hand-drawn student sketches to discover common answers.