Bidding-based multi-agent system for integrated process planning and scheduling: a data-mining and hybrid tabu-SA algorithm-oriented approach

2007 ◽  
Vol 38 (1-2) ◽  
pp. 163-175 ◽  
Author(s):  
Sanjay Kumar Shukla ◽  
M. K. Tiwari ◽  
Young Jun Son
Keyword(s):  
Data Mining ◽  
Process Planning ◽  
Multi Agent System ◽  
Integrated Process ◽  
Agent System ◽  
Planning And Scheduling ◽  
Multi Agent ◽  
Oriented Approach

A multi-agent system for the integration of process planning and scheduling using operation-based time-extended negotiation protocols

2010 ◽  
Vol 23 (5) ◽  
pp. 441-452 ◽  
Author(s):  
Izabel Cristina Zattar ◽  
João Carlos E. Ferreira ◽  
João Gabriel G. G. Rodrigues ◽  
Carlos Humberto B. de Sousa
Keyword(s):  
Process Planning ◽  
Multi Agent System ◽  
Agent System ◽  
Planning And Scheduling ◽  
Multi Agent ◽  
Negotiation Protocols

AN AGENT-ORIENTED APPROACH FOR IMAGE CLASSIFICATION WITH ICA-COLOR SIFT

2012 ◽  
Vol 21 (02) ◽  
pp. 1240003
Author(s):  
MOHAMMAD KHAZAB ◽  
DAN-NI AI ◽  
JEFFREY TWEEDALE ◽  
YEN-WEI CHEN ◽  
LAKHMI JAIN
Keyword(s):  
Image Processing ◽  
Image Classification ◽  
Classification Task ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent ◽  
Flexible Framework ◽  
Event Based ◽  
Oriented Approach

This paper discusses the research conducted on developing a Multi-Agent System (MAS) for solving an image classification task. The aim of this research is to equip agents in MAS with reusable autonomous capabilities. The system provides a flexible framework for developing the communication aspects within an agent-oriented architecture to program agents that dynamically acquire functionality at runtime using event based messaging. In this research agents are equipped with unique image processing capabilities and required to interact and cooperate to achieve the goal. Complementary research on a variety of agent tools (specifically JACK, JADE and CIAgent) and communication languages (ACL, KQML, FIPA and SOAP) has been reviewed to glean knowledge that enables these agents to adapt those capabilities. The system has generated encouraging results.

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