Automated negotiation for e-commerce decision making: A goal deliberated agent architecture for multi-strategy selection
Automated negotiation for e-commerce decision making: A goal deliberated agent architecture for multi-strategy selection
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DOI：
10.1016/j.dss.2015.02.012
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发表时间：
2015-05-01
影响因子：
7.5
通讯作者：
Dai, Xiaopei
中科院分区：
文献类型：
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作者：
Cao, Mukun;Luo, Xudong;Dai, Xiaopei
自动谈判在电子商务的动态交易中发挥着重要作用。其研究主要集中在谈判协议和策略设计。目前缺乏进一步的科学研究，迫切需要实施多策略选择，这对于人机谈判以取得更好的在线谈判结果至关重要。缺乏此类研究减缓了将自动谈判应用于现实世界问题的进程。为了解决这个关键问题，本文开发了一种多策略谈判代理系统。更具体地说，我们正式定义了代理的概念模型，并设计了其抽象软件架构。基于时间依赖策略和行为依赖策略的整合，我们还开发了多策略选择理论模型和算法。为了证明该模型算法的有效性，我们实现了一个原型并进行了大量实验。实验分析不仅证实了我们模型的有效性，而且还揭示了对人机谈判系统未来工作的一些见解，该系统将在未来的 B2C 电子商务中得到广泛应用。 (C) 2015 Elsevier B.V. 保留所有权利。
Automated negotiation plays an important role in dynamic trading in e-commerce. Its research largely focuses on negotiation protocol and strategy design. There is a paucity of further scientific investigation and a pressing need on the implementation of multi-strategy selection, which is crucially useful in human-computer negotiation to achieve better online negotiation outcomes. The lack of such studies has decelerated the process of applying automated negotiation to real world problems. To address the critical issue, this paper develops a multi-strategy negotiating agent system. More specifically, we formally define the agent's conceptual model, and design its abstract software architecture. Grounded on the integration of the time-dependent and behavior-dependent tactics, we also develop a multi-strategy selection theoretical model and algorithm. To demonstrate the effectiveness of this model algorithm, we implement a prototype and conduct numerous experiments. The experimental analysis not only confirms our model's effectiveness but also reveals some insights into future work about human-computer negotiation systems, which will be widely used in the future B2C e-commerce. (C) 2015 Elsevier B.V. All rights reserved.