Multi-Agent Fuzzy-Based Control Architecture for Autonomous Mobile Manipulators: Traditional Approaches and Multi-Agent Fuzzy-Based Approaches

Author(s):  
Abdelfetah Hentout ◽  
Mohamed Ayoub Messous ◽  
Saliha Oukid ◽  
Brahim Bouzouia
Author(s):  
Pragyan Nanda ◽  
Sritam Patnaik ◽  
Srikanta Patnaik

The fashion apparel industry is too diverse, volatile and uncertain due to the fast changing market scenario. Forecasting demands of consumers has become survival necessity for organizations dealing with this field. Many traditional approaches have been proposed for improving the computational time and accuracy of the forecasting system. However, most of the approaches have over-looked the uncertainty existing in the fashion apparel market due to certain unpredictable events such as new trends, new promotions and advertisements, sudden rise and fall in economic conditions and so on. In this chapter, an intelligent multi-agent based demand forecasting and replenishment system has been proposed that adopts features from nature-inspired computing for handling uncertainty of the fashion apparel industry. The proposed system is inspired from the group hunting behaviour of crocodiles such as they form temporary alliances with other crocodiles for their own benefit even after being territorial creatures.


Author(s):  
Franco Zambonelli ◽  
Nicholas R. Jennings ◽  
Michael Wooldridge

The multi-agent system paradigm introduces a number of new design/development issues when compared with more traditional approaches to software development and calls for the adoption of new software engineering abstractions. To this end, in this chapter, we elaborate on the potential of analyzing and architecting complex multi-agent systems in terms of computational organizations. Specifically, we identify the appropriate organizational abstractions that are central to the analysis and design of such systems, discuss their role and importance, and show how such abstractions are exploited in the context of the Gaia methodology for multi-agent systems development.


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