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A Distributed kWTA for Decentralized Auctions

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Neural Information Processing (ICONIP 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1962))

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Abstract

A distributed k-Winner-Take-All (kWTA) is presented in this paper. Its state-space model is given by

$$\begin{aligned} \frac{d}{dt}x_i(t) = - \left[ h(x_i(t)+u_i) - \frac{k}{n} + \beta \sum _{j \in \mathcal{N}_i} (x_i(t) - x_j(t)) \right] \\ z_i(x_i(t)) = h(x_i(t)+u_i) = \left\{ \begin{array}{ll} 1 &{} \text{ if }\, x_i(t) + u_i > 0 \\ 0 &{} \text{ if }\, x_i(t) + u_i \le 0 \end{array} \right. \end{aligned}$$

for \(i = 1, \cdots , n\). Here, \(u_i\)s and \(z_i\)s are the inputs and the outputs; \(\beta \) is a positive constant and \(\mathcal{N}_i\) is the neighbor set of the \(i^{th}\) node. If \(\beta \rightarrow 1\), both \(x_i(t)\) and \(z_i(t)\) converge in finite-time; \(z_i = 1\) if and only if \(u_i\) is one of the k largest inputs; and \(x_i \rightarrow -u_{\pi _{n-k}}\) (resp. \(-u_{\pi _{n-k+1}}\)) if \(x_i(0) \ll -1\) (resp. \(x_i(0) = 0\)). Accordingly, our kWTA is the best algorithm to be applied as a decentralized mechanism for sealed-bid first (resp. second) price auction if \(\beta \rightarrow \infty \), \(k = 1\) and \(u_i\)s are the bid prices. Compared with the conventional mechanism, our novel mechanism is able to protect the privacy of the bidders. Auctioneer can be ripped out. Bidders can only know the value of the payment and losing bidders cannot know who is the winner.

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Notes

  1. 1.

    In this paper, kWTA network, kWTA model and kWTA algorithm are used interchangeably.

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Acknowledgements

The work presented in this paper is supported in part by research grants from the Taiwan Ministry of Science and Technology (MOST) and National Science and Technology Council (NSTC) (110-2221-E-005-053, 111-2221-E-005-084 and 112-2221-E-005-076); and a Sustainable Technology Fund (STF) from Swiss Capital Group, Hong Kong.

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Sum, G., Sum, J., Chi-Sing Leung, A., Chang, J.C.C. (2024). A Distributed kWTA for Decentralized Auctions. In: Luo, B., Cheng, L., Wu, ZG., Li, H., Li, C. (eds) Neural Information Processing. ICONIP 2023. Communications in Computer and Information Science, vol 1962. Springer, Singapore. https://doi.org/10.1007/978-981-99-8132-8_11

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  • DOI: https://doi.org/10.1007/978-981-99-8132-8_11

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