Distributed Resource Allocation

2012 ◽  
Vol 4 (2) ◽  
pp. 49-62
Author(s):  
Kamal Moummadi ◽  
Rachida Abidar ◽  
Hicham Medromi
Keyword(s):  
Decision Support ◽  
Constraint Satisfaction ◽  
Constraint Programming ◽  
Constraint Satisfaction Problem ◽  
Data Communication ◽  
Communication Technologies ◽  
Multi Agent System ◽  
Agent System ◽  
Distributed Resource Allocation ◽  
Multi Agent

The growth of technological capabilities of mobile devices, the evolution of wireless communication technologies, and the maturity of embedded systems contributed to expand the Machine to machine (M2M) concept. M2M refers to data communication between machines without human intervention. The objective of this paper is to present the grand schemes of a model to be used in an agricultural Decision support System. The authors start by explaining and justifying the need for a hybrid system that uses both Multi-Agent System (MAS) and Constraint Programming (CP) paradigms. Then, the authors propose an approach for Constraint Programming and Multi-Agent System mixing based on controller agent concept. The authors present concrete constraints and agents to be used in a distributed architecture based on the proposed approach for M2M services and agricultural decision support. The platform is built in Java using general interfaces of both MAS and Constraint Satisfaction Problem (CSP) platforms and the conception is made by agent UML (AUML).

A Clustering Approach Based on Cooperative Agents to Improve Decision Support in ERP

2019 ◽  
pp. 1-18
Author(s):  
Nadjib Mesbahi ◽  
Okba Kazar ◽  
Saber Benharzallah ◽  
Merouane Zoubeidi ◽  
Djamil Rezki
Keyword(s):  
Decision Support ◽  
Intelligent Systems ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Cooperative Agents ◽  
Distributed Problem Solving ◽  
Multi Agent ◽  
Complete Set ◽  
Clustering Approach

Multi-agent systems (MAS) are a powerful technology for the design and implementation of autonomous intelligent systems that can handle distributed problem solving in a complex environment. This technology has played an important role in the development of data mining systems in the last decade, the purpose of which is to promote the extraction of information and knowledge from a large database and to make these systems more scalable. In this chapter, the authors present a clustering system based on cooperative agents through a centralized and common ERP database to improve decision support in ERP systems. To achieve this, they use multi-agent system paradigm to distribute the complexity of k-means algorithm in several autonomous entities called agents, whose goal is to group records or observations on similar objects classes. This will help business decision makers to make good decisions and provide a very good response time by the use of the multi-agent system. To implement the proposed architecture, it is more convenient to use the JADE platform while providing a complete set of services and have agents comply with the specifications FIPA.

A multi-agent system for meteorological radar data management and decision support

2009 ◽  
Vol 24 (11) ◽  
pp. 1264-1273 ◽  
Author(s):  
Ioannis N. Athanasiadis ◽  
Marios Milis ◽  
Pericles A. Mitkas ◽  
Silas C. Michaelides
Keyword(s):  
Decision Support ◽  
Data Management ◽  
Radar Data ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent ◽  
Meteorological Radar
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