M-PREF 2023: CALL FOR PAPERS

14th Multidisciplinary Workshop on Advances in Preference Handling

August 19, 20, or 21, 2023, Macau, S.A.R.
in conjunction with IJCAI 2023

https://sites.google.com/view/m-pref-2023/home
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IMPORTANT DATES

Paper submission deadline: May 1, 2023.
Author notification: June 5, 2023.
Camera ready version: June 20, 2023
M-PREF Workshop: August 19, 20, or 21, 2023


FORMAT

The program will consist of presentations of peer-reviewed papers,
invited talks, and a panel discussion. The workshop is a physical-only
event. At least one author from each accepted paper must register for
the workshop and travel to the IJCAI venue in person.


SUBMISSION

Researchers interested in preference handling from AI, OR, CS or other
computational fields may submit a paper, formatted according to the
IJCAI formatting instructions. The paper length is limited to 7 pages
plus 2 pages for references. Authors can choose between an anonymized
or non-anonymized submission. Multiple submissions of the same paper
to more than one IJCAI workshop are forbidden.

Formatting instructions: https://www.ijcai.org/authors_kit
Submission website: https://cmt3.research.microsoft.com/MPREF2023/


TOPICS

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/multicriteria systems
* Preference aggregation
* Reasoning with preferences
* Explaining preferences
* Applications of preferences
* Preference elicitation, statistical learning of preferences
* Preference representation and modeling
* Properties and semantics of preferences
* Uncertainty in preferences
* Practical preferences


WORKSHOP CHAIRS

Haris Aziz, UNSW Sydney, Australia
Ulrich Junker, France
Xinhang Lu, UNSW Sydney, Australia
Nicholas Mattei, Tulane University, USA
Andrea Passerini, University of Trento, Italy