[Apologies for Multiple Postings] ====================================================================== CALL FOR PAPERS:
10th Multidisciplinary Workshop on Advances in Preference Handling (M-PREF) New York, USA, during July 9-11, 2016 in conjunction with IJCAI-16. http://www.mpref-2016.preflib.org ====================================================================== Preference handling has become a flourishing topic. There are many interesting results, good examples for cross-fertilization between disciplines, and many new questions. Preferences are a central concept of decision making. As preferences are fundamental for the analysis of human choice behavior, they are becoming of increasing importance for computational fields such as artificial intelligence, databases, and human-computer interaction as well as for their respective applications. Preference models are needed in decision-support systems such as web-based recommender systems, in automated problem solvers such as configurators, and in autonomous systems such as Mars rovers. Nearly all areas of artificial intelligence deal with choice situations and can thus benefit from computational methods for handling preferences. Preference handling is also important for machine learning as preferences may guide learning behavior and be subject of dedicated learning methods. Moreover, social choice methods are also of key importance in computational domains such as multi-agent systems. This broadened scope of preferences leads to new types of preference models, new problems for applying preference structures, and new kinds of benefits. Preferences are studied in many areas of artificial intelligence such as knowledge representation & reasoning, multi-agent systems, game theory, social choice, constraint satisfaction, decision making, decision-theoretic planning, and beyond. Preferences are inherently a multi-disciplinary topic, of interest to economists, computer scientists, operations researchers, mathematicians and more. This workshop promotes this broadened scope of preference handling and continues a series of events on preference handling at AAAI-02, Dagstuhl in 2004, IJCAI-05, ECAI-06, VLDB-07, AAAI-08, ADT-09, ECAI-2010, ECAI-2012, IJCAI-13, AAAI-14, and IJCAI-15. At the previous edition of ADT-15 and LPNMR-15, which were co-located, one of the conclusions was that collaboration between the two areas can be very fruitful and should be fostered. The workshop will provide a forum for presenting advances in preference handling and for exchanging experiences between researchers facing similar questions, but coming from different fields. The workshop builds on the large number of AI researchers working on preference-related issues, but also seeks to attract researchers from databases, multi-criteria decision making, economics, etc. ====================================================================== TOPICS OF INTEREST ====================================================================== The workshop on Advances in Preference Handling addresses all computational aspects of preference handling. This includes methods for the elicitation, learning, modeling, representation, aggregation, and management of preferences and for reasoning about preferences. The workshop studies the usage of preferences in computational tasks from decision making, database querying, web search, personalized human-computer interaction, personalized recommender systems, e-commerce, multi-agent systems, game theory, social choice, combinatorial optimization, planning and robotics, automated problem solving, perception and natural language understanding and other computational tasks involving choices. The workshop seeks to improve the overall understanding of and best methodologies for preferences in order to realize their benefits in the multiplicity of tasks for which they are used. Another important goal is to provide cross-fertilization between the numerous sub-fields that work with preferences. * Preference handling in artificial intelligence * Preference handling in database systems * Preference handling in multiagent systems * Applications of preferences * Preference elicitation * Preference representation and modeling * Properties and semantics of preferences * Practical preferences ====================================================================== IMPORTANT DATES ====================================================================== May 1st, 2016: Workshop paper submission deadline. May 20th, 2016: Notification on workshop paper submissions. June 1st, 2016: Camera-ready copy due to organizers. July 9th, 10th, or 11th, 2016: M-PREF'16 Workshop. ===================================================================== SUBMISSION ===================================================================== Researchers interested in preference handling from AI, OR, DB, CS or other computational fields may submit a paper formatted according to the IJCAI Formatting Instructions and up to 6 pages in length + 1 page for references in PDF format. Workshop submissions and camera ready versions will be handled by EasyChair. Feel free to submit either anonymized or non-anonymized versions of your work. We have enabled anonymous reviewing so EasyChair will not reveal the authors unless you chose to do so in your submission. At least one author from each accepted paper must register for the workshop. Please see the IJCAI 2016 Website for information about accommodation and registration. Link to the paper submission page on EasyChair: https://easychair.org/conferences/?conf=mpref16 ====================================================================== WORKSHOP CHAIRS ====================================================================== Markus Endres, University of Augsburg (Germany) Nicholas Mattei, Optimization Research Group, Data 61 (NICTA) and University of New South Wales (Australia) Andreas Pfandler, TU Wien (Austria) and University of Siegen (Germany) ====================================================================== PROGRAM COMMITTEE ====================================================================== Thomas Allen, University of Kentucky Stefano Bistarelli, Università di Perugia Sylvain Bouveret, LIG - Grenoble INP Darius Braziunas, Kobo Inc. Jan Chomicki, University at Buffalo Paolo Ciaccia, University of Bologna James Delgrande, Simon Fraser University Matthias Ehrgott, Lancaster Gabor Erdelyi, Universitaet Siegen Johannes Fürnkranz, TU Darmstadt Judy Goldsmith, University of Kentucky Ulrich Junker Souhila Kaci, LIRMM Jérôme Lang, LAMSADE Nicolas Maudet, Université Pierre et Marie Curie Vincent Mousseau, LGI, Ecole Centrale Paris Patrice Perny, LIP6 Maria Silvia Pini, University of Padova Francesca Rossi, University of Padova and Harvard University Scott Sanner, University of Toronto Alexis Tsoukias, CNRS - LAMSADE Kristen Brent Venable, Tulane University and IHMC Paolo Viappiani, CNRS and LIP6, Univ Pierre et Marie Curie Toby Walsh, UNSW and Data61/NICTA Antonius Weinzierl, Vienna University of Technology Paul Weng, SYSU-CMU JIE Lirong Xia, RPI Neil Yorke-Smith, American University of Beirut Yong Zheng, DePaul University -- *Nicholas Mattei* Senior Researcher | Optimisation / Algorithmic Decision Theory Lecturer | University of New South Wales (UNSW) *DATA61 | CSIRO* E nicholas.mat...@nicta.com.au T +61 2 8306 0464 W www.nickmattei.net Neville Roach Laboratory (UNSW Campus), Locked Bag 6016, Sydney NSW 1466, Australia www.data61.csiro.au CSIRO’s Digital Productivity business unit and NICTA have joined forces to create digital powerhouse Data61
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