Open AccessPreference Handling in Combinatorial Domains: From AI to Social Choice
Author(s) -
Chevaleyre Yann,
Endriss Ulle,
Lang Jérôme,
Maudet Nicolas
Publication year - 2008
Publication title -
ai magazine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
DOI - 10.1609/aimag.v29i4.2201
Subject(s) - preference , group decision making , representation (politics) , fair division , context (archaeology) , voting , computer science , social choice theory , management science , field (mathematics) , artificial intelligence , resource (disambiguation) , space (punctuation) , data science , mathematical economics , mathematics , psychology , social psychology , political science , microeconomics , engineering , economics , pure mathematics , law , biology , operating system , paleontology , computer network , politics
In both individual and collective decision making, the space of alternatives from which the agent (or the group of agents) has to choose often has a combinatorial (or multiattribute) structure. We give an introduction to preference handling in combinatorial domains in the context of collective decision making and show that the considerable body of work on preference representation and elicitation that AI researchers have been working on for several years is particularly relevant. After giving an overview of languages for compact representation of preferences, we discuss problems in voting in combinatorial domains and then focus on multiagent resource allocation and fair division. These issues belong to a larger field, which is known as computational social choice and which brings together ideas from AI and social choice theory, to investigate mechanisms for collective decision making from a computational point of view. We conclude by briefly describing some of the other research topics studied in computational social choice.