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Nash Bargaining Via Flexible Budget Markets

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Algorithmic Aspects in Information and Management (AAIM 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5034))

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Abstract

In his seminal 1950 paper, John Nash defined the bargaining problem; the ensuing theory of bargaining lies today at the heart of game theory. In this work, we initiate an algorithmic study of Nash bargaining problems.

We consider a class of Nash bargaining problems whose solution can be stated as a convex program. For these problems, we show that there corresponds a market whose equilibrium allocations yield the solution to the convex program and hence the bargaining problem. For several of these markets, we give combinatorial, polynomial time algorithms, using the primal-dual paradigm.

Unlike the traditional Fisher market model, in which buyers spend a fixed amount of money, in these markets, each buyer declares a lower bound on the amount of utility she wishes to derive. The amount of money she actually spends is a specific function of this bound and the announced prices of goods.

Over the years, a fascinating theory has started forming around a convex program given by Eisenberg and Gale in 1959. Besides market equilibria, this theory touches on such disparate topics as TCP congestion control and efficient solvability of nonlinear programs by combinatorial means. Our work shows that the Nash bargaining problem fits harmoniously in this collage of ideas.

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Rudolf Fleischer Jinhui Xu

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© 2008 Springer-Verlag Berlin Heidelberg

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Vazirani, V.V. (2008). Nash Bargaining Via Flexible Budget Markets. In: Fleischer, R., Xu, J. (eds) Algorithmic Aspects in Information and Management. AAIM 2008. Lecture Notes in Computer Science, vol 5034. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68880-8_2

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  • DOI: https://doi.org/10.1007/978-3-540-68880-8_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68865-5

  • Online ISBN: 978-3-540-68880-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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