An execution time neural-CBR guidance assistant

NEUROCOMPUTING

卷:72

Article; Proceedings Paper

Corchado, Juan M.²  Bajo, Javier¹  De Paz, Juan F.²  Rodriguez, Sara² 

[1] Univ Salamanca, Escuela Univ Informat, Salamanca 37002, Spain

[2] Univ Salamanca, Dept Informat & Automat, E-37008 Salamanca, Spain

关键词: CBR systems;    Multi-agent system;    RFID;    Shopping malls;    Kohonen networks;    RTPW neural networks;   

DOI  :  10.1016/j.neucom.2008.08.020

来源: Elsevier

【 摘 要 】

This paper presents a novel Ambient Intelligence based solution for shopping assistance. The core of the proposal is a CBR system developed for guiding and advising users in shopping areas. The CBR incorporates a neural based planner that identifies the most adequate plan for a given user based on user profile and interests. The RTPW neural network is based on the Kohonen one, and incorporates an interesting modification that allows a solution or a plan to be reached much more rapidly. Furthermore, once an initial plan has been reached, it is possible to identify alternatives by taking restrictions into account. The CBR system has been embedded within a deliberative agent and interacts with interface and commercial agents, which facilitate the construction of intelligent environments. This hybrid application, which works on execution time, has been tested and the results of the investigation and its evaluation in a shopping mail are presented within this paper. (C) 2009 Elsevier B.V. All rights reserved.

【 授权许可】

Free