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Are Gross Substitutes a Substitute for Submodular Valuations?

Published: 18 July 2021 Publication History
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  • Abstract

    The class of gross substitutes (GS) set functions plays a central role in Economics and Computer Science. GS belongs to the hierarchy of complement free valuations introduced by Lehmann, Lehmann and Nisan, along with other prominent classes: GS ⊊ Submodular ⊊ XOS ⊊ Subadditive$. The GS class has always been more enigmatic than its counterpart classes, both in its definition and in its relation to the other classes. For example, while it is well understood how closely the Submodular, XOS and Subadditive classes (point-wise) approximate one another, approximability of these classes by GS remained wide open. In particular, the largest gap known between Submodular and GS valuations was some constant ratio smaller than 2. Our main result is the existence of a submodular valuation (one that is also budget additive) that cannot be approximated by GS within a ratio better than $Ømega(łog m/łogłog m), where m is the number of items. En route, we uncover a new symmetrization operation that preserves GS, which may be of independent interest. We show that our main result is tight with respect to budget additive valuations. However, whether GS approximates general submodular valuations within a poly-logarithmic factor remains open, even in the special case of concave of GS valuations (a subclass of Submodular containing budget additive). For concave of Rado valuations (Rado is a significant subclass of GS, containing, e.g., weighted matroid rank functions and OXS), we show approximability by GS within an O(łog2m) factor.

    References

    [1]
    Sepehr Assadi, Thomas Kesselheim, and Sahil Singla. 2021. Improved Truthful Mechanisms for Subadditive Combinatorial Auctions: Breaking the Logarithmic Barrier. In Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms (SODA). SIAM, 653--661.
    [2]
    Sepehr Assadi and Sahil Singla. 2019. Improved truthful mechanisms for combinatorial auctions with submodular bidders. In 2019 IEEE 60th Annual Symposium on Foundations of Computer Science (FOCS). IEEE, 233--248.
    [3]
    Lawrence M Ausubel and Paul R Milgrom. 2002. Ascending auctions with package bidding. The BE Journal of Theoretical Economics, Vol. 1, 1 (2002).
    [4]
    Ashwinkumar Badanidiyuru, Shahar Dobzinski, Hu Fu, Robert Kleinberg, Noam Nisan, and Tim Roughgarden. 2012. Sketching valuation functions. In Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms. SIAM, 1025--1035.
    [5]
    Maria-Florina Balcan and Nicholas JA Harvey. 2011. Learning submodular functions. In Proceedings of the forty-third annual ACM symposium on Theory of computing. 793--802.
    [6]
    Eric Balkanski and Renato Paes Leme. 2018. On the Construction of Substitutes. In Proceedings of the 2018 ACM Conference on Economics and Computation, Ithaca, NY, USA, June 18--22, 2018, É va Tardos, Edith Elkind, and Rakesh Vohra (Eds.). ACM, 643. https://doi.org/10.1145/3219166.3219184
    [7]
    Kshipra Bhawalkar and Tim Roughgarden. 2011. Welfare guarantees for combinatorial auctions with item bidding. In Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms. SIAM, 700--709.
    [8]
    Shahar Dobzinski. 2007. Two randomized mechanisms for combinatorial auctions. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques. Springer, 89--103.
    [9]
    Shahar Dobzinski, Noam Nisan, and Michael Schapira. 2010. Approximation algorithms for combinatorial auctions with complement-free bidders. Mathematics of Operations Research, Vol. 35, 1 (2010), 1--13.
    [10]
    A. Dress and W. Terhalle. 1995. Rewarding maps: On greedy optimization of set functions. Advances in Applied Mathematics, Vol. 16 (04 1995), 863--872. Issue 4.
    [11]
    Uriel Feige. 2009. On maximizing welfare when utility functions are subadditive. SIAM J. Comput., Vol. 39, 1 (2009), 122--142.
    [12]
    Michal Feldman, Hu Fu, Nick Gravin, and Brendan Lucier. 2013a. Simultaneous auctions are (almost) efficient. In Proceedings of the forty-fifth annual ACM symposium on Theory of computing. 201--210.
    [13]
    Vitaly Feldman, Pravesh Kothari, and Jan Vondrák. 2013b. Representation, approximation and learning of submodular functions using low-rank decision trees. In Conference on Learning Theory. PMLR, 711--740.
    [14]
    Jugal Garg, Edin Husic, and Laszlo A Vegh. 2020. Approximating Nash Social Welfare under Rado Valuations. arXiv preprint arXiv:2009.14793 (2020).
    [15]
    Michel X Goemans, Nicholas JA Harvey, Satoru Iwata, and Vahab Mirrokni. 2009. Approximating submodular functions everywhere. In Proceedings of the twentieth annual ACM-SIAM symposium on Discrete algorithms. SIAM, 535--544.
    [16]
    Faruk Gul and Ennio Stacchetti. 1999. Walrasian equilibrium with gross substitutes. Journal of Economic theory, Vol. 87, 1 (1999), 95--124.
    [17]
    Satoru Iwata, Lisa Fleischer, and Satoru Fujishige. 2001. A combinatorial strongly polynomial algorithm for minimizing submodular functions. Journal of the ACM (JACM), Vol. 48, 4 (2001), 761--777.
    [18]
    Alexander S Kelso Jr and Vincent P Crawford. 1982. Job matching, coalition formation, and gross substitutes. Econometrica: Journal of the Econometric Society (1982), 1483--1504.
    [19]
    Benny Lehmann, Daniel Lehmann, and Noam Nisan. 2006. Combinatorial auctions with decreasing marginal utilities. Games and Economic Behavior, Vol. 55, 2 (2006), 270--296.
    [20]
    Renato Paes Leme. 2017. Gross substitutability: An algorithmic survey. Games and Economic Behavior, Vol. 106 (2017), 294--316.
    [21]
    Kazuo Murota. 1996. Convexity and Steinitz's Exchange Property. In Integer Programming and Combinatorial Optimization, 5th International IPCO Conference, Vancouver, British Columbia, Canada, June 3--5, 1996, Proceedings (Lecture Notes in Computer Science, Vol. 1084), William H. Cunningham, S. Thomas McCormick, and Maurice Queyranne (Eds.). Springer, 260--274. https://doi.org/10.1007/3--540--61310--2_20
    [22]
    George L Nemhauser, Laurence A Wolsey, and Marshall L Fisher. 1978. An analysis of approximations for maximizing submodular set functions-I. Mathematical programming, Vol. 14, 1 (1978), 265--294.
    [23]
    Noam Nisan and Ilya Segal. 2006. The communication requirements of efficient allocations and supporting prices. Journal of Economic Theory, Vol. 129, 1 (2006), 192--224.
    [24]
    Michael Ostrovsky and Renato Paes Leme. 2015. Gross substitutes and endowed assignment valuations. Theoretical Economics, Vol. 10, 3 (2015), 853--865.
    [25]
    James Oxley. 2011. Matroid Theory (2nd ed.). Oxford Univerity Press.
    [26]
    Hans Reijnierse, Jos Potters, and Anita Gellekom. 2002. Verifying gross substitutability. Economic Theory, Vol. 20 (04 2002), 767--776. https://doi.org/10.1007/s00199-001-0248--5
    [27]
    GitHub Repository. 2020. https://github.com/feldmanmichal/TripletConditionGrossSubstitutes/.
    [28]
    Akiyoshi Shioura. 2012. Matroid rank functions and discrete concavity. Japan Journal of Industrial and Applied Mathematics, Vol. 29, 3 (1 Oct. 2012), 535--546. https://doi.org/10.1007/s13160-012-0082-0
    [29]
    Jan Vondrák. 2008. Optimal approximation for the submodular welfare problem in the value oracle model. In Proceedings of the fortieth annual ACM symposium on Theory of computing. 67--74.

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    cover image ACM Conferences
    EC '21: Proceedings of the 22nd ACM Conference on Economics and Computation
    July 2021
    950 pages
    ISBN:9781450385541
    DOI:10.1145/3465456
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    Published: 18 July 2021

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    1. gross substitutes
    2. valuation functions

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