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Auctioning Time: Truthful Auctions of Heterogeneous Divisible Goods

Published:05 January 2016Publication History
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Abstract

We consider the problem of auctioning time - a one-dimensional continuously-divisible heterogeneous good - among multiple agents. Applications include auctioning time for using a shared device, auctioning TV commercial slots, and more. Different agents may have different valuations for the different possible intervals; the goal is to maximize the aggregate utility. Agents are self-interested and may misrepresent their true valuation functions if this benefits them. Thus, we seek auctions that are truthful. Considering the case that each agent may obtain a single interval, the challenge is twofold, as we need to determine both where to slice the interval, and who gets what slice. We consider two settings: discrete and continuous. In the discrete setting, we are given a sequence of m indivisible elements (e1, …, em), and the auction must allocate each agent a consecutive subsequence of the elements. In the continuous setting, we are given a continuous, infinitely divisible interval, and the auction must allocate each agent a subinterval. The agents’ valuations are nonatomic measures on the interval. We show that, for both settings, the associated computational problem is NP-complete even under very restrictive assumptions. Hence, we provide approximation algorithms. For the discrete case, we provide a truthful auctioning mechanism that approximates the optimal welfare to within a log m factor. The mechanism works for arbitrary monotone valuations. For the continuous setting, we provide a truthful auctioning mechanism that approximates the optimal welfare to within an O(log n) factor (where n is the number of agents). Additionally, we provide a truthful 2-approximation mechanism for the case that all pieces must be of some fixed size.

References

  1. Yonatan Aumann, Yair Dombb, and Avinatan Hassidim. 2013. Computing socially-efficient cake divisions. In AAMAS. 343--350. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Xiaohui Bei, Ning Chen, Xia Hua, Biaoshuai Tao, and Endong Yang. 2012. Optimal proportional cake cutting with connected pieces. In AAAI.Google ScholarGoogle Scholar
  3. Steven J. Brams and Alan D. Taylor. 1996. Fair Division: From Cake Cutting to Dispute Resolution. Cambridge University Press, New York, NY.Google ScholarGoogle Scholar
  4. Yiling Chen, John Lai, David C. Parkes, and Ariel D. Procaccia. 2010. Truth, justice, and cake cutting. In AAAI.Google ScholarGoogle Scholar
  5. Yann Chevaleyre, Paul E. Dunne, Ulle Endriss, Jérôme Lang, Michel Lemaitre, Nicolas Maudet, Julian Padget, Steve Phelps, Juan A. Rodriguez-Aguilar, and Paulo Sousa. 2006. Issues in multiagent resource allocation. Informatica (Slovenia) 30, 1, 3--31.Google ScholarGoogle Scholar
  6. Peter Cramton. 1997. The FCC spectrum auctions: An early assessment. Journal of Economics & Management Strategy 6, 3, 431--495. DOI:http://dx.doi.org/10.1111/j.1430-9134.1997.00431.xGoogle ScholarGoogle ScholarCross RefCross Ref
  7. P. Cramton, Y. Shoham, and R. Steinberg. 2006. Combinatorial Auctions. MIT Press, Cambridge, MA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Shahar Dobzinski and Noam Nisan. 2007. Limitations of VCG-based mechanisms. In STOC. 338--344. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Jack Edmonds and Richard M. Karp. 1972. Theoretical improvements in algorithmic efficiency for network flow problems. Journal of the ACM 19, 2, 248--264. DOI:http://dx.doi.org/10.1145/321694.321699 Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Richard J. Gibbens and Frank P. Kelly. 1999. Resource pricing and the evolution of congestion control. Automatica 35, 12, 1969--1985. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Mingyu Guo and Vincent Conitzer. 2010. Strategy-proof allocation of multiple items between two agents without payments or priors. In AAMAS. 881--888. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Li Han, Chunzhi Su, Linpeng Tang, and Hongyang Zhang. 2011. On strategy-proof allocation without payments or priors. In WINE 2011, Lecture Notes in Computer Science, Vol. 7090. Springer, Berlin. 182--193. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Ramesh Johari and John N. Tsitsiklis. 2009. Efficiency of scalar-parameterized mechanisms. Operations Research 57, 823--839. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Ilan Kremer and Kjell G. Nyborg. 2004. Divisible-good auctions: The role of allocation rules. RAND Journal of Economics 147--159.Google ScholarGoogle Scholar
  15. Benny Lehmann, Daniel J. Lehmann, and Noam Nisan. 2001. Combinatorial auctions with decreasing marginal utilities. In ACM Conference on Electronic Commerce. ACM, New York, NY, 18--28. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Rajiv T. Maheswaran and Tamer Basar. 2003. Nash equilibrium and decentralized negotiation in auctioning divisible resources. Group Decision and Negotiation 13, 2003.Google ScholarGoogle Scholar
  17. Avishay Maya and Noam Nisan. 2012. Incentive compatible two player cake cutting. In WINE 2012, Lecture Notes in Computer Science, Vol. 7695. Springer, Berlin, 170--183. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Elchanan Mossel and Omer Tamuz. 2010. Truthful fair division. In Algorithmic Game Theory. Springer, 288--299. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Noam Nisan. 2000. Bidding and allocation in combinatorial auctions. In ACM Conference on Electronic Commerce. 1--12. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Noam Nisan, Jason Bayer, Deepak Chandra, Tal Franji, Robert Gardner, Yossi Matias, Neil Rhodes, Misha Seltzer, Danny Tom, Hal Varian, and Dan Zigmond. 2009. Google’s auction for TV Ads. In Automata, Languages and Programming, Lecture Notes in Computer Science, Vol. 5556. Springer, Berlin, 309--327. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Noam Nisan and Amir Ronen. 1999. Algorithmic mechanism design (extended abstract). In STOC. 129--140. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Noam Nisan and Amir Ronen. 2000. Computationally feasible VCG mechanisms. In ACM Conference on Electronic Commerce. 242--252. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Noam Nisan, Tim Roughgarden, Eva Tardos, and Vijay V. Vazirani. 2007. Algorithmic Game Theory. Cambridge University Press, New York, NY. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Ariel D. Procaccia. 2013. Cake cutting: Not just child’s play. Communications of the ACM 56, 7, 78--87. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Jack Robertson and William Webb. 1998. Cake-Cutting Algorithms: Be Fair If You Can. A. K. Peters, Ltd., Natick, MA.Google ScholarGoogle Scholar
  26. Michael H. Rothkopf, Aleksandar Pekeč, and Ronald M. Harstad. 1998. Computationally manageable combinational auctions. Management Science 44, 8, 1131--1147. DOI:http://dx.doi.org/10.1287/mnsc.44.8.1131 Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Moshe Tennenholtz. 2000. Some tractable combinatorial auctions. In AAAI/IAAI. 98--103. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Sichao Yang and Bruce Hajek. 2007. VCG-Kelly mechanisms for allocation of divisible goods: Adapting VCG mechanisms to one-dimensional signals. IEEE Journal on Selected Areas in Communications 25, 6, 1237--1243. Google ScholarGoogle ScholarDigital LibraryDigital Library

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      • Published in

        cover image ACM Transactions on Economics and Computation
        ACM Transactions on Economics and Computation  Volume 4, Issue 1
        December 2015
        169 pages
        ISSN:2167-8375
        EISSN:2167-8383
        DOI:10.1145/2852252
        Issue’s Table of Contents

        Copyright © 2016 ACM

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        Publication History

        • Published: 5 January 2016
        • Accepted: 1 January 2015
        • Revised: 1 November 2014
        • Received: 1 June 2014
        Published in teac Volume 4, Issue 1

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