### Abstract

We study the following online problem: at each time unit, one of m identical items is offered for sale. Bidders arrive and depart dynamically, and each bidder is interested in winning one item between his arrival and departure. Our goal is to design truthful mechanisms that maximize the welfare, the sum of the utilities of winning bidders. We first consider this problem under the assumption that the private information for each bidder is his value for getting an item. In this model constant-competitive mechanisms are known, but we observe that these mechanisms suffer from the following disadvantage: a bidder might learn his payment only when he departs. We argue that these mechanism are essentially unusable, because they impose several seemingly undesirable requirements on any implementation of the mechanisms. To crystalize these issues, we define the notions of prompt and tardy mechanisms. We present two prompt mechanisms, one deterministic and the other randomized, that guarantee a constant competitive ratio. We show that our deterministic mechanism is optimal for this setting. We then study a model in which both the value and the departure time are private information. While in the deterministic setting only a trivial competitive ratio can be guaranteed, we use randomization to obtain a prompt truthful -competitive mechanism. We then show that no truthful randomized mechanism can achieve a ratio better than in this model.

Original language | English (US) |
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Title of host publication | Algorithmic Game Theory - First International Symposium, SAGT 2008, Proceedings |

Pages | 170-181 |

Number of pages | 12 |

Volume | 4997 LNCS |

DOIs | |

State | Published - 2008 |

Event | 1st International Symposium on Algorithmic Game Theory, SAGT 2008 - Paderborn, Germany Duration: Apr 30 2008 → May 2 2008 |

### Publication series

Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 4997 LNCS |

ISSN (Print) | 03029743 |

ISSN (Electronic) | 16113349 |

### Other

Other | 1st International Symposium on Algorithmic Game Theory, SAGT 2008 |
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Country | Germany |

City | Paderborn |

Period | 4/30/08 → 5/2/08 |

### Fingerprint

### ASJC Scopus subject areas

- Computer Science(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Theoretical Computer Science

### Cite this

*Algorithmic Game Theory - First International Symposium, SAGT 2008, Proceedings*(Vol. 4997 LNCS, pp. 170-181). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4997 LNCS). https://doi.org/10.1007/978-3-540-79309-0_16

**Prompt mechanisms for online auctions.** / Cole, Richard; Dobzinski, Shahar; Fleischer, Lisa.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Algorithmic Game Theory - First International Symposium, SAGT 2008, Proceedings.*vol. 4997 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4997 LNCS, pp. 170-181, 1st International Symposium on Algorithmic Game Theory, SAGT 2008, Paderborn, Germany, 4/30/08. https://doi.org/10.1007/978-3-540-79309-0_16

}

TY - GEN

T1 - Prompt mechanisms for online auctions

AU - Cole, Richard

AU - Dobzinski, Shahar

AU - Fleischer, Lisa

PY - 2008

Y1 - 2008

N2 - We study the following online problem: at each time unit, one of m identical items is offered for sale. Bidders arrive and depart dynamically, and each bidder is interested in winning one item between his arrival and departure. Our goal is to design truthful mechanisms that maximize the welfare, the sum of the utilities of winning bidders. We first consider this problem under the assumption that the private information for each bidder is his value for getting an item. In this model constant-competitive mechanisms are known, but we observe that these mechanisms suffer from the following disadvantage: a bidder might learn his payment only when he departs. We argue that these mechanism are essentially unusable, because they impose several seemingly undesirable requirements on any implementation of the mechanisms. To crystalize these issues, we define the notions of prompt and tardy mechanisms. We present two prompt mechanisms, one deterministic and the other randomized, that guarantee a constant competitive ratio. We show that our deterministic mechanism is optimal for this setting. We then study a model in which both the value and the departure time are private information. While in the deterministic setting only a trivial competitive ratio can be guaranteed, we use randomization to obtain a prompt truthful -competitive mechanism. We then show that no truthful randomized mechanism can achieve a ratio better than in this model.

AB - We study the following online problem: at each time unit, one of m identical items is offered for sale. Bidders arrive and depart dynamically, and each bidder is interested in winning one item between his arrival and departure. Our goal is to design truthful mechanisms that maximize the welfare, the sum of the utilities of winning bidders. We first consider this problem under the assumption that the private information for each bidder is his value for getting an item. In this model constant-competitive mechanisms are known, but we observe that these mechanisms suffer from the following disadvantage: a bidder might learn his payment only when he departs. We argue that these mechanism are essentially unusable, because they impose several seemingly undesirable requirements on any implementation of the mechanisms. To crystalize these issues, we define the notions of prompt and tardy mechanisms. We present two prompt mechanisms, one deterministic and the other randomized, that guarantee a constant competitive ratio. We show that our deterministic mechanism is optimal for this setting. We then study a model in which both the value and the departure time are private information. While in the deterministic setting only a trivial competitive ratio can be guaranteed, we use randomization to obtain a prompt truthful -competitive mechanism. We then show that no truthful randomized mechanism can achieve a ratio better than in this model.

UR - http://www.scopus.com/inward/record.url?scp=44449104166&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=44449104166&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-79309-0_16

DO - 10.1007/978-3-540-79309-0_16

M3 - Conference contribution

SN - 3540793089

SN - 9783540793083

VL - 4997 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 170

EP - 181

BT - Algorithmic Game Theory - First International Symposium, SAGT 2008, Proceedings

ER -