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10.5555/3020751.3020768guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
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Market making with decreasing utility for information

Published: 23 July 2014 Publication History

Abstract

We study information elicitation in cost-function-based combinatorial prediction markets when the market maker's utility for information decreases over time. In the sudden revelation setting, it is known that some piece of information will be revealed to traders, and the market maker wishes to prevent guaranteed profits for trading on the sure information. In the gradual decrease setting, the market maker's utility for (partial) information decreases continuously over time. We design adaptive cost functions for both settings which: (1) preserve the information previously gathered in the market; (2) eliminate (or diminish) rewards to traders for the publicly revealed information; (3) leave the reward structure unaffected for other information; and (4) maintain the market maker's worst-case loss. Our constructions utilize mixed Bregman divergence, which matches our notion of utility for information.

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Published In

cover image Guide Proceedings
UAI'14: Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence
July 2014
926 pages
ISBN:9780974903910
  • Editors:
  • Nevin Zhang,
  • Jin Tian

Sponsors

  • Google Inc.
  • Artificial Intelligence Journal
  • IBMR: IBM Research
  • Microsoft Research: Microsoft Research
  • Facebook: Facebook

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AUAI Press

Arlington, Virginia, United States

Publication History

Published: 23 July 2014

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