2016 FLAIRS AI Track

After an early dominance in AI, especially in NLP, approaches based on engineered knowledge-resources such as rule bases and ontologies modeling (part of) the world, the statistical winter set in in the 1980s. Fueled by increased computing power, statistics-based replacements for modeling the world, including machine-learning and neural networks, lead to early successes before they hit their ceiling and resulted in algorithmic arms races. To get AI out of these trenches and back into mobile warfare, knowledge-based methods have not only been being paid lipservice to in the many "semantic" revolutions, but actual applications have been built, often with complementary methodologies that paired statistical and knowledge-based solutions.

The scope of the track includes research, proof-of-concept and industry applications in the area of knowledge-based AI, i.e. systems whose functionality is informed by computational knowledge resources (ontologies, lexicons, semantic networks and/or knowledge bases). While the knowledge-based AI is often juxtaposed to the statistics-based AI, we see the contrast as unnecessarily exclusionary, in that systems combining the intuitive directness of knowledge representation with the efficiency of statistics-based computation have distinct advantages.

To showcase recent knowledge-based theories, methodologies, and applications in AI and to foster new approaches of this kind, also those paired with statistical and machine-learning approaches.

The scope of the track includes research, proof-of-concept and industry applications in the area of knowledge-based AI, i.e. systems whose functionality is informed by computational knowledge resources (ontologies, lexicons, semantic networks and/or knowledge bases). While the knowledge-based AI is often juxtaposed to the statistics-based AI, we see the contrast as unnecessarily exclusionary, in that systems combining the intuitive directness of knowledge representation with the efficiency of statistical approximation have distinct advantages.

Papers and contributions are encouraged for any work relating to Knowledge-Based AI. Topics of interest may include (but are in no way limited to):

Note: We invite original papers (i.e. work not previously submitted, in submission, or to be submitted to another conference during the reviewing process).

Interested authors should format their papers according to AAAI formatting guidelines. The papers should be original work (i.e., not submitted, in submission, or submitted to another conference while in review). Papers should not exceed 6 pages (4 pages for a poster) and are due by November 16, 2015. For FLAIRS-29, the 2016 conference, the reviewing is a double blind process. Fake author names and affiliations must be used on submitted papers to provide double-blind reviewing. Papers must be submittcoued as PDF through the EasyChair conference system, which can be accessed through the main conference web site (http://www.flairs-29.info/). Note: do not use a fake name for your EasyChair login - your EasyChair account information is hidden from reviewers. Authors should indicate the [your track name] special track for submissions. The proceedings of FLAIRS will be published by the AAAI. Authors of accepted papers will be required to sign a form transferring copyright of their contribution to AAAI. FLAIRS requires that there be at least one full author registration per paper.

Please, check the website http://www.flairs-29.info/ for further information.

Papers will be refereed and all accepted papers will appear in the conference proceedings, which will be published by AAAI Press.  

Questions regarding the Knowledge-Based AI Special Track should be addressed to the track co-chairs:

Questions regarding Special Tracks should be addressed to Zdravko Markov, markovz@ccsu.edu

Conference Chair: William (Bill) Eberle, Tennessee Technological University, USA (WEberle@tntech.edu)

Program Co-Chairs: Zdravko Markov, Central Connecticut State University, USA (markovz@ccsu.edu)
Ingrid Russell, University of Hartford, USA (irussell@hartford.edu)

Special Tracks Coordinator: Vasile Rus, The University of Memphis, USA (vrus@memphis.edu)

Paper submission site: follow the link for submissions at http://www.flairs-29.info/
FLAIRS-29 conference web page: http://www.flairs-29.info/ 
Florida AI Research Society (FLAIRS): http://www.flairs.com