TY - GEN
T1 - Strategy-proof and non-wasteful multi-unit auction via social network
AU - Kawasaki, Takehiro
AU - Barrot, Nathanaël
AU - Takanashi, Seiji
AU - Todo, Taiki
AU - Yokoo, Makoto
N1 - Funding Information:
This work is partially supported by JSPS KAKENHI Grants JP17H00761 and JP17H04695, and JST SICORP JP-MJSC1607.
Funding Information:
This work is partially supported by JSPS KAKENHI Grants JP17H00761 and JP17H04695, and JST SICORP JPMJSC1607.
Publisher Copyright:
Copyright © 2020, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2020
Y1 - 2020
N2 - Auctions via social network, pioneered by Li et al. (2017), have been attracting considerable attention in the literature of mechanism design for auctions. However, no known mechanism has satisfied strategy-proofness, non-deficit, non-wastefulness, and individual rationality for the multi-unit unit-demand auction, except for some naïve ones. In this paper, we first propose a mechanism that satisfies all the above properties. We then make a comprehensive comparison with two naïve mechanisms, showing that the proposed mechanism dominates them in social surplus, seller's revenue, and incentive of buyers for truth-telling. We also analyze the characteristics of the social surplus and the revenue achieved by the proposed mechanism, including the constant approximability of the worst-case efficiency loss and the complexity of optimizing revenue from the seller's perspective.
AB - Auctions via social network, pioneered by Li et al. (2017), have been attracting considerable attention in the literature of mechanism design for auctions. However, no known mechanism has satisfied strategy-proofness, non-deficit, non-wastefulness, and individual rationality for the multi-unit unit-demand auction, except for some naïve ones. In this paper, we first propose a mechanism that satisfies all the above properties. We then make a comprehensive comparison with two naïve mechanisms, showing that the proposed mechanism dominates them in social surplus, seller's revenue, and incentive of buyers for truth-telling. We also analyze the characteristics of the social surplus and the revenue achieved by the proposed mechanism, including the constant approximability of the worst-case efficiency loss and the complexity of optimizing revenue from the seller's perspective.
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M3 - Conference contribution
AN - SCOPUS:85091753567
T3 - AAAI 2020 - 34th AAAI Conference on Artificial Intelligence
SP - 2062
EP - 2069
BT - AAAI 2020 - 34th AAAI Conference on Artificial Intelligence
PB - AAAI Press
T2 - 34th AAAI Conference on Artificial Intelligence, AAAI 2020
Y2 - 7 February 2020 through 12 February 2020
ER -