FUN-Agent: 2020年人类竞赛的参赛者

R. Geraghty, James Hale, S. Sen, Timothy S. Kroecker
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引用次数: 1

摘要

最近,工业界和普通民众对人类与人工智能合作的未来潜力产生了极大的兴趣[20]。学术研究人员长期以来一直在推动对等水平和特设人类代理协作新模式的前沿[10;22]。我们对代表人类用户与其他人类和自主代理谈判交易的代理的研究特别感兴趣[12;16;18]。在这里,我们展示了我们的代理进入2020年自动谈判代理竞赛(ANAC)的人类联盟的对话方面的设计。我们讨论了我们的代理如何利用会话和谈判策略,模仿人类谈判中使用的策略,以最大限度地发挥其作为模拟街头小贩的效用。我们利用口头影响策略,提供价格,增加人力便利来吸引买家,建立信任并阻止剥削。此外,我们还讨论了我们进行的一些内部测试的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FUN-Agent: A 2020 HUMAINE Competition Entrant
Of late, there has been a significant surge of interest in industry and the general populace about future potential of human-AI collaboration [20]. Academic researchers have been pushing the frontier of new modalities of peer-level and ad-hoc human agent collaboration [10;22] for a longer period. We have been particularly interested in research on agents representing human users in negotiating deals with other human and autonomous agents [12;16;18]. Here we present the design for the conversational aspect of our agent entry into the HUMAINE League of the 2020 Automated Negotiation Agent Competition (ANAC). We discuss how our agent utilizes conversational and negotiation strategies, that mimic those used in human negotiations, to maximize its utility as a simulated street vendor. We leverage verbal influence tactics, offer pricing, and increasing human convenience to entice the buyer, build trust and discourage exploitation. Additionally, we discuss the results of some in-house testing we conducted.
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