NDLI: Aggregating value ranges: preference elicitation and truthfulness

Content Provider	Springer Nature Link
Author	Farfel, Joseph Conitzer, Vincent
Copyright Year	2009
Abstract	We study the case where agents have preferences over ranges (intervals) of values, and we wish to elicit and aggregate these preferences. For example, consider a set of climatologist agents who are asked for their predictions for the increase in temperature between 2009 and 2100. Each climatologist submits a range, and from these ranges we must construct an aggregate range. What rule should we use for constructing the aggregate range? One issue in such settings is that an agent (climatologist) may misreport her range to make the aggregate range coincide more closely with her own (true) most-preferred range. We extend the theory of single-peaked preferences from points to ranges to obtain a rule (the median-of-ranges rule) that is strategy-proof under a condition on preferences. We then introduce and analyze a natural class of algorithms for approximately eliciting a median range from multiple agents. We also show sufficient conditions under which such an approximate elicitation algorithm still incentivizes agents to answer truthfully. Finally, we consider the possibility that ranges can be refined when the topic is more completely specified (for example, the increase in temperature on the North Pole given the failure of future climate pacts). We give a framework and algorithms for selectively specifying the topic further based on queries to agents.
Starting Page	127
Ending Page	150
Page Count	24
File Format	PDF
ISSN	13872532
Journal	Autonomous Agents and Multi-Agent Systems
Volume Number	22
Issue Number	1
e-ISSN	15737454
Language	English
Publisher	Springer US
Publisher Date	2009-11-10
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	User Interfaces and Human Computer Interaction Software Engineering/Programming and Operating Systems Computing Methodologies Computer Systems Organization and Communication Networks Artificial Intelligence (incl. Robotics)
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence

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