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摘要翻译：
首届交易代理比赛(TAC)于2000年6月22日至7月8日举行。TAC的设计目的是在电子市场的复杂领域中创建一个基准问题，并激励研究人员对一个共同的任务应用独特的方法。本文介绍了ATTac-2000，它是TAC中的第一个完成器。ATTac-2000使用了一个原则性的投标策略，其中包括几个适应性要素。除了在竞争中的成功之外，孤立的实证结果表明了Attac-2000自适应策略的鲁棒性和有效性。
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英文标题：
《ATTac-2000: An Adaptive Autonomous Bidding Agent》
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作者：
M. Kearns, M. L. Littman, S. Singh, P. Stone
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最新提交年份：
2011
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分类信息：
一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
The First Trading Agent Competition (TAC) was held from June 22nd to July 8th, 2000. TAC was designed to create a benchmark problem in the complex domain of e-marketplaces and to motivate researchers to apply unique approaches to a common task. This article describes ATTac-2000, the first-place finisher in TAC. ATTac-2000 uses a principled bidding strategy that includes several elements of adaptivity. In addition to the success at the competition, isolated empirical results are presented indicating the robustness and effectiveness of ATTac-2000's adaptive strategy.
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PDF链接：
https://arxiv.org/pdf/1106.0678
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