Human-Machine Collective Intelligence Environment for Decision Support: Conceptual and Technological Design

Author(s):  
Alexander Smirnov ◽  
Andrew Ponomarev
Procedia CIRP ◽  
2020 ◽  
Vol 90 ◽  
pp. 594-599
Author(s):  
Mickaël Bettinelli ◽  
Michel Occello ◽  
Damien Genthial ◽  
Daniel Brissaud

Author(s):  
Alexander Smirnov ◽  
Tatiana Levashova ◽  
Andrew Ponomarev

Introduction: Due to the development of information and communication technologies and artificial intelligence, human-machine computing systems are becoming more widely used. However, in the vast majority of developments in this area, a human, in fact, plays the role of a “computing device”, who can only handle requests of a certain kind. Thus, human creativity and the ability to (self-)organize are largely discarded. Purpose: Developing a decision support concept based on the use of human-machine collective intelligence. Analyzing the current state of the problem in the field of constructing flexible human-machine systems. Proposing a conceptual model of the environment based on which decision support systems can be created. Results: A conceptual model of decision support is proposed based on human-machine collective intelligence. Its central concepts are: a) the problem at whose solution the human-machine collective activity is aimed, b) the collective of machines and people interacting through the environment to solve the problem, c) the process model which describes the decision support process in terms of information collection development and evaluation of alternatives. Practical relevance: The developed model can be a base to create a new class of decision support systems leveraging the self-organization potential of human-machine collectives.


Author(s):  
Yuliana Perez-Gallardo ◽  
Giner Alor-Hernandez ◽  
Guillermo Cortes-Robles

With the implementation of CBIR paradigms and Collective Intelligence into Web 2.0 application, CRM 2.0 can be improved by providing a new strategy for presenting products or services. This integration materializes a link where customers have the ability to enrich their search before the purchase; to effectively compare products, and to clarify their preferences. Finally, it is important to underline that the proposed integration represents a decision support in the feedback phase of CRM.


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