Multi-agent neural business control system

被引：15

作者：

Lourdes Borrajo, M. ^{[2
]}

Corchado, Juan M. ^{[1
]}

Corchado, Emilio S. ^{[3
]}

Pellicer, Maria A. ^{[3
]}

Bajo, Javier ^{[1
]}

机构：

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

[2] Univ Vigo, Dept Informat, Escuela Super Ingn Informat, Orense 32004, Spain

[3] Univ Burgos, Dept Ingn Civil, Esc Politecn Super, Burgos 09006, Spain

来源：

INFORMATION SCIENCES | 2010年 / 180卷 / 06期

关键词：

Agents technology; Business control system; Case-based reasoning; Maximum Likelihood Hebbian Learning; Reasoning; Experience management; AGENTS; MODEL;

D O I：

10.1016/j.ins.2009.11.028

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Small to medium sized companies require a business control mechanism in order to monitor their modus operandi and analyse whether they are achieving their goals. A tool for the decision Support process was developed based on a multi-agent system that incorporates a case-based reasoning system and automates the business control process. The case-based reasoning system automates the organization of cases and the retrieval stage by means of a Maximum Likelihood Hebbian Learning-based method, an extension of the Principal Component Analysis which groups similar cases by automatically identifying clusters in a data set in an unsupervised mode The multi-agent system was tested with 22 small and medium sized companies in the textile sector located in the northwest of Spain during 29 months. and the results obtained have been very satisfactory (C) 2009 Elsevier Inc. All rights reserved.

引用

页码：911 / 927

页数：17

共 50 条

[21] A Multi-Agent Role-Based System for Business Intelligence
Mabrouk, Tamer F.
El-Sherbiny, Mohamed M.
Guirguis, Shawkat K.
Shawky, Ayman Y.
INNOVATIONS AND ADVANCES IN COMPUTER SCIENCES AND ENGINEERING, 2010, : 203 - 208
[22] A Neural Network Approach Applied to Multi-Agent Optimal Control
Onken, Derek
Nurbekyan, Levon
Li, Xingjian
Fung, Samy Wu
Osher, Stanley
Ruthotto, Lars
2021 EUROPEAN CONTROL CONFERENCE (ECC), 2021, : 1036 - 1041
[23] Neural control, multi-agent navigation and virtual reality of robots
Timofeev, AV
NONLINEAR CONTROL SYSTEMS 2001, VOLS 1-3, 2002, : 1543 - 1548
[24] Designing a Multi-agent Control System for a Reconfigurable Manufacturing System
Matei, Alexandru
Pirvu, Bogdan Constantin
Petruse, Radu Emanuil
Candea, Ciprian
Zamfirescu, Bala Constantin
12TH INTERNATIONAL WORKSHOP ON SERVICE ORIENTED, HOLONIC AND MULTI-AGENT MANUFACTURING SYSTEMS FOR INDUSTRY OF THE FUTURE, SOHOMA 2022, 2023, 1083 : 434 - 445
[25] The control of Distributed Generation System using Multi-Agent System
Xu, Qun
Jia, Xiaobo
He, Liqin
ICEIE 2010 - 2010 International Conference on Electronics and Information Engineering, Proceedings, 2010, 1
[26] Prevention and control model of enterprise business risk based on multi-agent
Information Management Institute of ShanDong Economic University, China
J. Convergence Inf. Technol., 7 (19):
[27] A Multi-Agent System for Autonomous Control of Game Parameters
Pons, Luc
Bernon, Carole
2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013), 2013, : 583 - 588
[28] Towards a Cognitive Multi-Agent System for Building Control
Kollmann, Stefan
Siafara, Lydia C.
Schaat, Samer
Wendt, Alexander
7TH ANNUAL INTERNATIONAL CONFERENCE ON BIOLOGICALLY INSPIRED COGNITIVE ARCHITECTURES, (BICA 2016), 2016, 88 : 191 - 197
[29] Communication and Control Algorithms for a Heterogenous Multi-agent System
Dinu, Andrei Cristian
Ancuta, Paul-Nicolae
Zafiu, Victor-Marin
INTERNATIONAL CONFERENCE ON RELIABLE SYSTEMS ENGINEERING (ICORSE) - 2021, 2022, 305 : 223 - 228
[30] SARA: A multi-agent system for collaborative command and control
Nelson, KS
Penner, RR
Soken, NH
PROCEEDINGS OF THE THIRTY-FIRST HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES, VOL VII: SOFTWARE TECHNOLOGY TRACK, 1998, : 784 - 793

← 1 2 3 4 5 →