Providing high-quality service to all users is a difficult and inefficient strategy for e-commerce providers, especially when Web servers experience overload conditions that cause increased response time and request rejections, leading to user frustration and reduced revenue. In an e-commerce system, customer Web sessions have differing values for service providers. These tend to: give preference to customer Web sessions that are likely to bring more profit by providing better service quality. This paper proposes a reinforcement-learning based adaptive e-commerce system model that adapts the service quality level for different Web sessions within the customer’s navigation in order to maximize total profit. The e-commerce system is considered as an electronic supply chain which includes a network of basic e- providers used to supply e-commerce services for end customers. The learner agent noted as e-commerce supply chain manager (ECSCM) agent allocates a service quality level to the customer’s request based on his/her navigation pattern in the e-commerce Website and selects an optimized combination of service providers to respond to the customer’s request. To evaluate the proposed model, a multi agent framework composed of three agent types, the ECSCM agent, customer agent (buyer/browser) and service provider agent, is employed. Experimental results show that the proposed model improves total profits through cost reduction and revenue enhancement simultaneously and encourages customers to purchase from the Website through service quality adaptation.

中文翻译：

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基于强化学习的电子商务网站自适应服务质量管理模型

为所有用户提供高质量的服务对于电子商务提供商来说是一种困难且效率低下的策略，尤其是当 Web 服务器遇到过载情况时，会导致响应时间增加和请求拒绝，从而导致用户沮丧和收入减少。在电子商务系统中，客户 Web 会话对于服务提供商具有不同的价值。这些倾向于： 优先考虑可能通过提供更好的服务质量带来更多利润的客户 Web 会话。本文提出了一种基于强化学习的自适应电子商务系统模型，该模型针对客户导航中的不同 Web 会话调整服务质量水平，以实现总利润最大化。电子商务系统被认为是一个电子供应链，其中包括用于为最终客户提供电子商务服务的基本电子商务供应商网络。学习者代理被称为电子商务供应链经理 (ECSCM) 代理，根据他/她在电子商务网站中的导航模式为客户的请求分配服务质量级别，并选择服务提供商的优化组合来响应客户的请求。要求。为了评估所提出的模型，采用了由三种代理类型组成的多代理框架，即 ECSCM 代理、客户代理（买方/浏览器）和服务提供商代理。实验结果表明，所提出的模型通过同时降低成本和增加收入来提高总利润，并通过服务质量适应来鼓励客户从网站购买。