Abstract
We consider mechanisms for markets that are two-sided and have agents with multi-dimensional strategic spaces on at least one side. The agents of the market are strategic and act to optimize their own utilities, while the mechanism designer aims to optimize a social goal, i.e., the gain from trade. We focus on one example of this setting motivated by a foreseeable privacy-aware future form of online advertising.
Recently, it has been suggested that markets of user information built around information brokers could be introduced to the online advertising ecosystem to overcome online privacy concerns. Such markets give users control over which data gets shared in online advertising exchanges. We describe a model for the above form of online advertising and design two mechanisms for this model. The first is a deterministic mechanism which is related to the vast literature on mechanism design through trade reduction and allows agents with a multi-dimensional strategic space. The second is a randomized mechanism that can handle a more general version of the model. We provide theoretical analyses of our mechanisms and study their performance using simulations based on real-world data.
This work was supported by the Horizon 2020 funded project TYPES (Project number: 653449. Call Identifier H2020-DS-2014-1).
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Notes
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We often refer to agents with a multi-dimensional strategic space as multi-dimensional agents.
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- 3.
Here and throughout the paper, a reference to domination of strategies should be understood as a reference to weak domination. We never refer to strong domination.
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Feldman, M., Gonen, R. (2018). Removal and Threshold Pricing: Truthful Two-Sided Markets with Multi-dimensional Participants. In: Deng, X. (eds) Algorithmic Game Theory. SAGT 2018. Lecture Notes in Computer Science(), vol 11059. Springer, Cham. https://doi.org/10.1007/978-3-319-99660-8_15
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