有交易成本的扩散拍卖设计

IF 2 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS
Bin Li, Dong Hao, Dengji Zhao
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引用次数: 0

摘要

我们研究的是由中介市场驱动的多单位拍卖,在中介市场中,所有交易都由中介处理,并产生一定的成本。市场中的每个中间商都拥有一组私人买家,所有中间商之间都是联网的。我们的目标是激励中间商将拍卖信息分享给他们能够接触到的个人,包括他们的私人买家和邻近的中间商,从而使更多潜在买家能够参与拍卖。为此,我们建立了一个基于扩散的拍卖框架,以处理中间商之间的交易成本和战略互动。场景中经典的维克里-克拉克-格罗夫斯(VCG)机制可以获得最大的社会福利,但它会减少卖方的收入,甚至导致赤字。为了解决收入问题,我们开发了两种减少赤字的策略,并在此基础上确定了一个称为临界邻域拍卖(CNA)的扩散拍卖系列。CNA 不仅能使社会福利最大化,还能消除卖方的所有赤字。此外,CNA 的收益不低于有/无中介的 VCG 机制的收益。这是第一套具有福利和收益优势的扩散拍卖,可以处理多个项目和交易成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Diffusion auction design with transaction costs

Diffusion auction design with transaction costs

We study multi-unit auctions powered by intermediated markets, where all transactions are processed by intermediaries and incur certain costs. Each intermediary in the market owns a private set of buyers and all intermediaries are networked with each other. Our goal is to incentivize the intermediaries to share the auction information to individuals they can reach, including their private buyers and neighboring intermediaries, so that more potential buyers are able to participate in the auction. To this end, we build a diffusion-based auction framework to handle the transaction costs and the strategic interactions between intermediaries. The classic Vickrey-Clarke-Groves (VCG) mechanism within the scenario can obtain the maximum social welfare, but it can decrease the seller’s revenue or even lead to a deficit. To overcome the revenue issue, we develop two deficit reduction strategies, based on which a family of diffusion auctions called Critical Neighborhood Auctions (CNA) is identified. The CNA not only maximizes the social welfare, but also eliminates all the seller’s deficits. Moreover, the revenue given by the CNA is no less than the revenue given by the VCG mechanism with/without intermediaries. This is the first set of diffusion auctions with welfare and revenue advantages that can handle multiple items and transaction costs.

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来源期刊
Autonomous Agents and Multi-Agent Systems
Autonomous Agents and Multi-Agent Systems 工程技术-计算机:人工智能
CiteScore
6.00
自引率
5.30%
发文量
48
审稿时长
>12 weeks
期刊介绍: This is the official journal of the International Foundation for Autonomous Agents and Multi-Agent Systems. It provides a leading forum for disseminating significant original research results in the foundations, theory, development, analysis, and applications of autonomous agents and multi-agent systems. Coverage in Autonomous Agents and Multi-Agent Systems includes, but is not limited to: Agent decision-making architectures and their evaluation, including: cognitive models; knowledge representation; logics for agency; ontological reasoning; planning (single and multi-agent); reasoning (single and multi-agent) Cooperation and teamwork, including: distributed problem solving; human-robot/agent interaction; multi-user/multi-virtual-agent interaction; coalition formation; coordination Agent communication languages, including: their semantics, pragmatics, and implementation; agent communication protocols and conversations; agent commitments; speech act theory Ontologies for agent systems, agents and the semantic web, agents and semantic web services, Grid-based systems, and service-oriented computing Agent societies and societal issues, including: artificial social systems; environments, organizations and institutions; ethical and legal issues; privacy, safety and security; trust, reliability and reputation Agent-based system development, including: agent development techniques, tools and environments; agent programming languages; agent specification or validation languages Agent-based simulation, including: emergent behavior; participatory simulation; simulation techniques, tools and environments; social simulation Agreement technologies, including: argumentation; collective decision making; judgment aggregation and belief merging; negotiation; norms Economic paradigms, including: auction and mechanism design; bargaining and negotiation; economically-motivated agents; game theory (cooperative and non-cooperative); social choice and voting Learning agents, including: computational architectures for learning agents; evolution, adaptation; multi-agent learning. Robotic agents, including: integrated perception, cognition, and action; cognitive robotics; robot planning (including action and motion planning); multi-robot systems. Virtual agents, including: agents in games and virtual environments; companion and coaching agents; modeling personality, emotions; multimodal interaction; verbal and non-verbal expressiveness Significant, novel applications of agent technology Comprehensive reviews and authoritative tutorials of research and practice in agent systems Comprehensive and authoritative reviews of books dealing with agents and multi-agent systems.
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