Strategyproof exchange with multiple private endowments

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

12 被引用数 (Scopus)

抄録

We study a mechanism design problem for exchange economies where each agent is initially endowed with a set of indivisible goods and side payments arc not allowed. We assume each agent can withhold some endowments. as well as misreport her preference. Under this assumption, strategyproofness requires that for each agent, reporting her true preference with revealing all her endowments is a dominant strategy, and thus implies individual rationality. Our objective in this paper is to analyze the effect of such private ownership in exchange economies with multiple endowments. As fundamental results, we first show that the revelation principle holds under a natural assumption and that strategyproofness and Pareto efficiency are incompatible even under the lexicographic preference domain. We then propose a class of exchange rules, each of which has a corresponding directed graph to prescribe possible trades, and provide necessary and sufficient conditions on the graph structure so that they satisfy strategyproofness.

本文言語英語
ホスト出版物のタイトルProceedings of the 28th AAAI Conference on Artificial Intelligence and the 26th Innovative Applications of Artificial Intelligence Conference and the 5th Symposium on Educational Advances in Artificial Intelligence
出版社AI Access Foundation
ページ805-811
ページ数7
ISBN(電子版)9781577356776
出版ステータス出版済み - 2014
イベント28th AAAI Conference on Artificial Intelligence, AAAI 2014, 26th Innovative Applications of Artificial Intelligence Conference, IAAI 2014 and the 5th Symposium on Educational Advances in Artificial Intelligence, EAAI 2014 - Quebec City, カナダ
継続期間: 7 27 20147 31 2014

出版物シリーズ

名前Proceedings of the National Conference on Artificial Intelligence
1

その他

その他28th AAAI Conference on Artificial Intelligence, AAAI 2014, 26th Innovative Applications of Artificial Intelligence Conference, IAAI 2014 and the 5th Symposium on Educational Advances in Artificial Intelligence, EAAI 2014
国/地域カナダ
CityQuebec City
Period7/27/147/31/14

All Science Journal Classification (ASJC) codes

  • ソフトウェア
  • 人工知能

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