Modeling of User Preference Based on Agent for Service Selection

HUANG Hai-qing; ZHANG Ping; ZHANG Xi-wen

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Modeling of User Preference Based on Agent for Service Selection

更新时间：2025-07-16

- Modeling of User Preference Based on Agent for Service Selection
- Acta Electronica Sinica Vol. 34, Issue S1, Pages: 2537-2540(2006)
- 作者机构：
  
  1. 北京邮电大学,北京,100876
  2. 航天科工集团二院,北京,100854
  3. 北京邮电大学,北京,100876
  4. 航天科工集团二院,北京,100854
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN91
- Published：2006
- 稿件说明：
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HUANG Hai-qing, ZHANG Ping, ZHANG Xi-wen. Modeling of User Preference Based on Agent for Service Selection[J]. Acta Electronica Sinica, 2006, 34(S1): 2537-2540.
DOI：

HUANG Hai-qing, ZHANG Ping, ZHANG Xi-wen. Modeling of User Preference Based on Agent for Service Selection[J]. Acta Electronica Sinica, 2006, 34(S1): 2537-2540. DOI：

摘要

将马尔可夫判决过程和强化学习算法相结合

给出了异构无线网络环境下用户业务偏好评估模型的技术框架.为动态环境下用户需求的感知、量化和适配特征的研究提供了基本的数学描述

对解决用户体验的评价问题和业务与业务环境的适配问题提供了新的研究思路.仿真结果表明构建的模型能够在满足用户偏好的前提下智能选择业务.

Abstract

We present a technical architecture for user preference model

and show the nature of the problem represented within a Markov Decision Process combined with adaptive reinforcement learning algorithm.We provide a possible candidate solution for user modeling dynamically to satisfy the users expected preference based on minimal or missing information

it is also a exploration for the evaluation of the user experience when selecting service providers.Simulations of the representative user models show that the adaptive reinforcement learning solutions are effective.

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