Multi-agent Information Retrieval in Heterogeneous Industrial Automation Environments

Author(s):  
Stephan Pech ◽  
Peter Goehner
Author(s):  
Tarek Ben Mena ◽  
Narjès Bellamine-Ben Saoud ◽  
Mohamed Ben Ahmed ◽  
Bernard Pavard

This chapter aims to define context notion for multi-agent systems (MAS). Starting from the state of the art on context in different disciplines, we present context as a generic and abstract notion. We argue that context depends on three characteristics: domain, entity, and problem. By specifying this definition with MAS, we initially consider context from an extensional point of view as three components—actant, role, and situation—and then from an intensional one, which represents the context model for agents in MAS which consist of information on environment, other objects, agents, and relations between them. Therefore, we underline a new way of representing agent knowledge, building context on this knowledge, and using it. Furthermore, we prove the applicability of contextual agent solution for other research fields, particularly in personalized information retrieval by taking into account as agents: crawlers and as objects: documents.


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