Designing decision-making agents for electronic markets

随着电子商务在当今社会中的作用越来越大，智能计算机系统（代理）被要求在电子市场中代表用户做出决定，在电子市场中购买、销售和交易商品、服务和信息。这样的决策需要详细了解用户的偏好；因此，学习用户偏好和不完整信息推理的有效和准确的方法是这项工作的关键组成部分。在代理与其他代理谈判或竞争的情况下（代表其他用户行动），额外的关注包括有效谈判策略的设计和对对手偏好和目标建模的能力。

With the increased role of electronic commerce in today's society, intelligent computer systems (agents) are being called upon to make decisions on a user's behalf in electronic markets where goods, services and information are purchased, sold and traded. Such decision making requires detailed knowledge of the user's preferences; therefore, efficient and accurate methods for learning about the user's preferences and for reasoning with incomplete information are critical components of this work. In the case of settings where an agent is negotiating with or competing against other agents (acting on the behalf of other users), additional concerns include the design of effective negotiation strategies and the ability to model the opponent's preferences and goals.