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Reserve price strategy for seller agent in multiple simultaneous auctions

机译：多个同时拍卖中卖方代理的底价策略

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摘要

Internet auction is popular due to the flexibility and convenience that it offers to consumers. In online auctions, sellers are confronted with the dilemma of deciding the best reserve price for the items to be auctioned off. In an auction site such as eBay, one can always find the same item being sold by multiple sellers in different auctions. Determining this reserve price is not a straightforward decision process due to the complexity and vagueness of the online auction environment. Setting the reserve price too high may result in no sale whilst setting the reserve price too low may result in a sale with low profit. The main focus of this paper is to analyze the performance of the selling agents with varying pricing strategy when offering item for auctions. The strategy could be categorized as low, intermediate, high, and random based on its sellers' types. Our study showed that the use of these strategies produced significant drawbacks with negative impacts towards the overall selling upshots. To counteract these shortcomings, we develop an autonomous seller agent using a heuristic decision making framework. To derive the best reserve price, several constraints are considered including the number of competitors, the number of bidders, the auction length, and the profit that the seller desires. This paper presents the design, implementation and evaluation of our selling algorithm that a seller agent can use for auctioning homogeneous goods among multiple overlapping English auctions. In this work, we modeled our market simulation for a single unit auction using an independent private value framework with dynamic participation entry.
机译：互联网拍卖之所以受欢迎，是因为它为消费者提供了灵活性和便利性。在在线拍卖中，卖家面临着为待拍卖品确定最佳底价的难题。在诸如eBay之类的拍卖网站上，人们总是可以找到由不同卖家在不同拍卖中出售的同一物品。由于在线拍卖环境的复杂性和模糊性，确定这个底价不是一个简单的决定过程。将底价设置得太高可能会导致无人出售，而将底价设置得太低可能会导致低利润的销售。本文的主要重点是分析在提供拍卖项目时采用不同定价策略的销售代理商的绩效。根据卖家的类型，该策略可以分为低，中，高和随机。我们的研究表明，使用这些策略会产生明显的缺陷，并对总体销售结果产生负面影响。为了弥补这些缺点，我们使用启发式决策框架开发了自主卖方代理。为了获得最佳底价，要考虑几个约束条件，包括竞争者的数量，投标者的数量，拍卖时间和卖方期望的利润。本文介绍了我们的销售算法的设计，实现和评估，卖方代理可以使用该算法在多次重叠的英国拍卖中拍卖同类商品。在这项工作中，我们使用具有动态参与项的独立私有价值框架为单个单位拍卖建模了市场模拟。

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