9th Multidisciplinary Workshop on
Advances in Preference Handling
TOPICS OF INTEREST
The workshop on Advances in Preferences 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, e-commerce, multi-agent systems, 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 the benefits of preferences for those tasks. Another important goal is to provide cross-fertilization between different fields.
Preference handling in Artificial Intelligence
Qualitative decision theory
Non-monotonic reasoning
Preferences in logic programming
Preferences for soft constraints in constraint satisfaction
Preferences for search and optimization
Preferences for AI planning
Preferences reasoning about action and causality
Preference logic
Preference handling in data-base systems
Preference query languages for SQL and XML
Algebraic and cost-based optimization of preference queries
Top-k algorithms and cost models
Ranking relational data and rank-aware query processing
Skyline query evaluation
Preference management and repositories
Personalized search engines
Preference recommender systems
Preference handling in multiagent systems
Game theory
(Combinatorial) auctions and exchanges
Social choice, voting, and other rating/ranking systems
Mechanism design and incentive compatibility
Applications of preferences
Web search
Decision making
Combinatorial optimization and other problem solving tasks
Personalized human-computer interaction
Personalized recommendation systems
e-commerce and m-commerce
Preference elicitation
Preference elicitation in multi-agent systems
Preference elicitation with incentive-compatibility
Learning of preferences
User preference mining
Revision of preferences
Preference representation and modeling
Linear and non-linear utility representations
Multiple criteria/attributes
Qualitative decision theory
Graphical models
Logical representations
Soft constraints
Relations between qualitative and quantitative approaches
Properties and semantics of preferences
Preference and choice
Preference composition, merging, and aggregation
Incomplete or inconsistent preferences
Intransitive indifference
Reasoning about preferences
Comparison of approaches, cross-fertilization, interdisciplinary work