A complexity approach for core-selecting exchange under conditionally lexicographic preferences

Etsushi Fujita, Julien Lesca, Akihisa Sonoda, Taiki Todo, Makoto Yokoo

Research output: Contribution to journalArticle

Abstract

Core-selection is a crucial property of rules in the literature of resource allocation. It is also desirable, from the perspective of mechanism design, to address the incentive of agents to cheat by misreporting their preferences. this paper investigates the exchange problem where (i) each agent is initially endowed with (possibly multiple) indivisible goods, (ii) agents' preferences are assumed to be conditionally lexicographic, and (iii) side payments are prohibited. We propose an exchange rule called augmented top-trading-cycles (ATTC), based on the original TTC procedure. We first show that ATTC is core-selecting and runs in polynomial time with respect to the number of goods. We then show that finding a beneficial misreport under ATTC is NP-hard. We finally clarify relationship of misreporting with splitting and hiding, two different types of manipulations, under ATTC.

Original languageEnglish
Pages (from-to)515-555
Number of pages41
JournalJournal of Artificial Intelligence Research
Volume63
DOIs
Publication statusPublished - Nov 1 2018

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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