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Elicitating, modeling, and processing uncertain human preferences for software agents in electronic negotiations: An empirical study

机译:在电子谈判中激发,建模和处理不确定的人类对软件代理的偏爱:一项实证研究

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Transaction costs in electronic business may become marginal, since negotiation processes can be assigned to software agents which act autonomously on behalf of their human principals. This advantage makes electronic negotiations highly appealing to actors in various e-business areas, including online auctions and product configuration negotiations. However, software agents can negotiate appropriately only if the preferences of their principals are explicitly available. While this task has been acknowledged as crucial challenge, it has only rarely been investigated how preferences of human principals can be extracted and modeled. This paper addresses this research gap by suggesting, implementing, and empirically testing a preference elicitation method that is based on fuzzy set theory and accounts for the impreciseness and subjectivity of preferences. Our findings indicate that the proposed method is suited for elicitating fuzzy set based preferences. Furthermore, the fuzzy preference model can project human decisions more accurately than a traditional, crisp approach.
机译:电子商务的交易成本可能变得微不足道,因为可以将协商过程分配给代表其人工委托人自主行动的软件代理。这种优势使电子谈判对包括在线拍卖和产品配置谈判在内的各个电子商务领域的参与者都具有极大的吸引力。但是,只有当其委托人的首选项明确可用时,软件代理才能进行适当的协商。尽管这项任务被认为是至关重要的挑战,但很少研究如何提取和建模人类主体的偏好。本文通过建议,实施和经验检验基于模糊集理论并说明了偏好的不精确性和主观性的偏好启发方法,解决了这一研究空白。我们的发现表明,所提出的方法适合于引起基于模糊集的偏好。此外,与传统的清晰方法相比,模糊偏好模型可以更准确地预测人为决策。

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