Results of the First Annual Human-Agent League of the Automated Negotiating Agents Competition
Results of the First Annual Human-Agent League of the Automated Negotiating Agents Competition
复制标题
第一届年度人类代理联盟自动谈判代理竞赛结果
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
C. Jonker
中科院分区：
文献类型：
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作者：
Johnathan Mell;J. Gratch;T. Baarslag;Reyhan Aydoğan;C. Jonker
我们提出了ANAC的第一届年度人类智能体联盟的结果。通过向整个研究界引入一个新的人类代理谈判平台，我们促进了人类感知代理的新进展。这已经成功地推动了代理设计的信封，并创建了一个有用的人-代理交互数据的语料库。我们的研究结果表明，各种代理提交，他们不同的策略有不同的结果，对许多措施的谈判。这些代理人的方法特有的人类谈判的问题，包括用户建模，投标策略，融洽的技术，和战略讨价还价。一些特工在信息收集或情感表达方面采用了先进的战术，并获得了比对手更多的分数，而另一些特工则被他们的伴侣认为更“讨人喜欢”。
We present the results of the first annual Human-Agent League of ANAC. By introducing a new human-agent negotiating platform to the research community at large, we facilitated new advancements in human-aware agents. This has succeeded in pushing the envelope in agent design, and creating a corpus of useful human-agent interaction data. Our results indicate a variety of agents were submitted, and that their varying strategies had distinct outcomes on many measures of the negotiation. These agents approach the problems endemic to human negotiation, including user modeling, bidding strategy, rapport techniques, and strategic bargaining. Some agents employed advanced tactics in information gathering or emotional displays and gained more points than their opponents, while others were considered more "likeable" by their partners.