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CALL FOR PARTICIPATION
14th Multidisciplinary Workshop on
Advances in Preference Handling (M-PREF 2023)
August 21, 2023, Macao, S.A.R
in conjunction with IJCAI 2023
https://sites.google.com/view/m-pref-2023/home
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DESCRIPTION
Human-centered AI requires that AI systems are able to adapt to
humans, to understand the preferences underlying human choice
behavior, and to take them into account when interacting with humans
or when acting on their behalf. Preference models are needed in
decision-support systems such as web-based recommender systems, in
digital assistants and chatbots, 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
while gaining new capabilities such as explainability and revisability
of choices. 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 of key
importance in computational domains such as multi-agent
systems. Preferences are studied in many areas of artificial
intelligence such as knowledge representation & reasoning, multi-agent
systems, game theory, computational social choice, constraint
satisfaction, logic programming and non-monotonic reasoning, decision
making, decision-theoretic planning, and beyond. Preferences are
inherently a multi-disciplinary topic, of interest to economists,
computer scientists (including AI, databases, and human-computer
interaction), operations researchers, mathematicians and more.
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.
TOPICS
This broad set of application areas leads to new types of preference
models, new problems for applying preference structures, and new kinds
of benefits. The workshop on Advances in Preference Handling studies
these questions and addresses all computational aspects of preference
handling. This includes methods for the elicitation, learning,
modeling, representation, aggregation, and management of preferences
as well as methods 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, computational social choice, combinatorial
optimization, automated problem solving, non-monotonic reasoning,
planning and robotics, perception and natural language understanding,
and other computational tasks involving choices. A particular
challenge consists in using preferences for explaining decisions and
for counterfactual reasoning based on hypothetical preference
change. Another challenge is to explore new application areas for
preferences such as sustainable development and digital healthcare
systems. 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
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 and learning
- Preference representation and modeling
- Properties and semantics of preferences
- Practical preferences
PROGRAM
The following schedule is tentative. Please check the following web
page for last minute changes:
https://sites.google.com/view/m-pref-2023/program
09:10am - 09:20am (UTC + 8) Welcome by Organizers
09:20am - 10:00am (UTC + 8) Technical Session
9:20am - 9:40am Paper Presentation:
Guanbao Yu, Umer Siddique, Paul Weng on "Fair Deep Reinforcement
Learning with Preferential Treatment"
9:40am - 10am Paper Presentation:
Yong Zheng and David Xuejun Wang on "Hybrid Multi-Criteria Preference
Ranking by Subsorting"
10am - 10:15am (UTC + 8) Break
10:15am - 11:15am (UTC + 8) Invited Talk:
Piotr Faliszewski on "Method of Equal Shares for Participatory
Budgeting in Practice"
11:15am - 11:45am (UTC + 8) Break
11:45am - 12:45am (UTC + 8) Technical Session
11:45am - 12:05pm Paper Presentation:
Haris Aziz, Xinhang Lu, Mashbat Suzuki, Jeremy Vollen, and Toby Walsh
on "Best-of-Both-Worlds Fairness in Committee Voting"
12:05pm - 12:25pm Contributed Talk:
Xinhang Lu on "Approval-Based Voting with Mixed Goods"
12:25pm - 12:45pm Contributed Talk:
Margot Herin on "Learning Compact Preference Representations based on
Choquet Integrals"
12:45pm - 2pm (UTC + 8) Lunch Break
2pm - 3pm (UTC + 8) Invited Panel
"Fairness: From Social Choice to Machine Learning" ft. Nisarg Shah and
Lirong Xia with Moderator Toby Walsh
3pm - 3:30pm (UTC + 8) Break
3:30pm - 4:30pm (UTC + 8) Invited Talk:
Warut Suksompong on "Weighted Fair Division: Additive Preferences and
Beyond"
4:30pm - 5pm (UTC + 8) Closing:
Ulrich Junker on "Why did we start the M-PREF workshop series?"
ATTENDANCE
Participants can register for W07 - 14th Multidisciplinary Workshop on
Advances in Preference Handling (M-PREF 2023) in the IJCAI 2023
registration system:
https://registration.ijcai.org/auth/login
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
WORKSHOP URL
https://sites.google.com/view/m-pref-2023/home
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