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Characterizing truthful multi-armed bandit mechanisms (2009)
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| Venue: | In ACM-EC |
| Citations: | 30 - 1 self |
BibTeX
@INPROCEEDINGS{Babaioff09characterizingtruthful,
author = {Moshe Babaioff and Yogeshwer Sharma and Aleksandrs Slivkins},
title = {Characterizing truthful multi-armed bandit mechanisms},
booktitle = {In ACM-EC},
year = {2009},
pages = {79--88}
}
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Abstract
We consider a multi-round auction setting motivated by payper-click auctions for Internet advertising. In each round the auctioneer selects an advertiser and shows her ad, which is then either clicked or not. An advertiser derives value from clicks; the value of a click is her private information. Initially, neither the auctioneer nor the advertisers have any information about the likelihood of clicks on the advertisements. The auctioneer’s goal is to design a (dominant strategies) truthful mechanism that (approximately) maximizes the social welfare. If the advertisers bid their true private values, our problem is equivalent to the multi-armed bandit problem, and thus can be viewed as a strategic version of the latter. In particular, for both problems the quality of an algorithm can be characterized by regret, the difference in social welfare between the algorithm and the benchmark which always selects the same“best”advertisement. We investigate how the design of multi-armed bandit algorithms is affected by the restriction that the resulting mechanism must be truthful. We find that truthful mechanisms have certain strong structural properties – essentially, they must separate exploration from exploitation – and they incur much higher regret than the optimal multi-armed bandit algorithms. Moreover, we provide a truthful mechanism which (essentially) matches our lower bound on regret.
Keyphrases
truthful multi-armed bandit mechanism social welfare truthful mechanism multi-armed bandit algorithm internet advertising private information multi-round auction multi-armed bandit problem true private value payper-click auction auctioneer goal certain strong structural property dominant strategy optimal multi-armed bandit algorithm strategic version
