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Auctions with Interdependence and SOS: Improved Approximation

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Algorithmic Game Theory (SAGT 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12885))

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Abstract

Interdependent values make basic auction design tasks – in particular maximizing welfare truthfully in single-item auctions – quite challenging. Eden et al. recently established that if bidders’ valuation functions are submodular over their signals (a.k.a. SOS), a truthful 4-approximation to the optimal welfare exists. We show existence of a mechanism that is truthful and achieves a tight 2-approximation to the optimal welfare when signals are binary. Our mechanism is randomized and assigns bidders only 0 or \(\frac{1}{2}\) probabilities of winning the item. Our results utilize properties of submodular set functions, and extend to matroid settings.

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Notes

  1. 1.

    The algorithm runs in time polynomial in its input size, which consists of set functions over n elements and so is exponential in n.

  2. 2.

    Our algorithm has two iterations: At \(s_1=0\), an appropriate pair is not found and so the highest bidder (bidder 1) wins the item with probability \(\frac{1}{2}\), which is propagated forward to this bidder at \(s_1=1\). At \(s_1=1\), an appropriate pair is again not found and so the highest bidder (bidder 2) wins the item with probability \(\frac{1}{2}\).

  3. 3.

    This notation is not to be confused with the value for a set of items S; in our model there is a single item, and a bidder’s interdependent value for it is determined by the set of signals, i.e., which subset of signals is “on”.

  4. 4.

    As mentioned above, submodularity over signals is not to be confused with submodularity over items in combinatorial auctions.

  5. 5.

    Note the difference from dominant-strategy IC, in which this guarantee should hold no matter how other bidders report.

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Correspondence to Ameer Amer or Inbal Talgam-Cohen .

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Amer, A., Talgam-Cohen, I. (2021). Auctions with Interdependence and SOS: Improved Approximation. In: Caragiannis, I., Hansen, K.A. (eds) Algorithmic Game Theory. SAGT 2021. Lecture Notes in Computer Science(), vol 12885. Springer, Cham. https://doi.org/10.1007/978-3-030-85947-3_3

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  • DOI: https://doi.org/10.1007/978-3-030-85947-3_3

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