A POMDP Based Approach to Optimally Select Sellers in Electronic Marketplaces
A POMDP Based Approach to Optimally Select Sellers in Electronic Marketplaces
复制标题
基于 POMDP 的电子市场卖家优化选择方法
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Jie Zhang
中科院分区：
文献类型：
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作者：
Athirai Aravazhi Irissappane;F. Oliehoek;Jie Zhang
在电子市场中选择卖家是一项繁琐的任务，我们可能希望将其委托给代理商。人们已经提出了许多构建此类代理的方法，它们建立在不同的基础（决策理论、信任模型）之上，并利用不同的信息（与卖家的直接经验、卖家的声誉、被称为顾问的其他买家的可信度等）。在本文中，我们提出了 SALE POMDP，这是一种基于 POMDP 决策理论框架的新方法。它可以实现信息获取和利用行为的最佳权衡，最终目标是最大限度地提高买家满意度。该模型的一个独特功能是它允许向顾问询问其他顾问的可信度。我们将该模型表示为分解的 POMDP，从而能够使用计算上更有效的解决方法。 ART 测试平台的评估表明，SALE POMDP 比传统信任模型更有效地平衡了获取更多信息的成本和收益，从而带来更多收益。实验还表明，与之前基于 POMDP 的方法相比，它对于欺骗性顾问来说更加稳健，并且分解公式可以解决相当大的卖方选择问题实例。
Selecting a seller in e-markets is a tedious task that we might want to delegate to an agent. Many approaches to constructing such agents have been proposed, building upon different foundations (decision theory, trust modeling) and making use of different information (direct experience with sellers, reputation of sellers, trustworthiness of other buyers called advisors, etc.). In this paper, we propose the SALE POMDP, a new approach based on the decision-theoretic framework of POMDPs. It enables optimal trade-offs of information gaining and exploiting actions, with the ultimate goal of maximizing buyer satisfaction. A unique feature of the model is that it allows querying advisors about the trustworthiness of other advisors. We represent the model as a factored POMDP, thereby enabling the use of computationally more efficient solution methods. Evaluation on the ART testbed demonstrates that SALE POMDP balances the cost of obtaining and benefit of more information more effectively, leading to more earnings, than traditional trust models. Experiments also show that it is more robust to deceptive advisors than a previous POMDP based approach, and that the factored formulation allows the solution of reasonably large instances of seller selection problems.