Personalizing Information Retrieval with Multi-agent Systems

2004 ◽  
pp. 77-91 ◽  
Author(s):  
Fabrício Enembreck ◽  
Jean-Paul Barthès ◽  
Braulio Coelho Ávila
Keyword(s):  
Information Retrieval ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

Towards a Context Definition for Multi-Agent Systems

2011 ◽  
pp. 286-307
Author(s):  
Tarek Ben Mena ◽  
Narjès Bellamine-Ben Saoud ◽  
Mohamed Ben Ahmed ◽  
Bernard Pavard
Keyword(s):  
Information Retrieval ◽  
Knowledge Building ◽  
Point Of View ◽  
Multi Agent Systems ◽  
Context Model ◽  
Agent Systems ◽  
Research Fields ◽  
Present Context ◽  
Multi Agent ◽  
Abstract Notion

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.

scholarly journals Learning in multi-agent systems

2001 ◽  
Vol 16 (3) ◽  
pp. 277-284 ◽  
Author(s):  
EDUARDO ALONSO ◽  
MARK D'INVERNO ◽  
DANIEL KUDENKO ◽  
MICHAEL LUCK ◽  
JASON NOBLE
Keyword(s):  
Artificial Intelligence ◽  
Information Retrieval ◽  
Community Research ◽  
Intelligence Community ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Software Programs

In recent years, multi-agent systems (MASs) have received increasing attention in the artificial intelligence community. Research in multi-agent systems involves the investigation of autonomous, rational and flexible behaviour of entities such as software programs or robots, and their interaction and coordination in such diverse areas as robotics (Kitano et al., 1997), information retrieval and management (Klusch, 1999), and simulation (Gilbert & Conte, 1995). When designing agent systems, it is impossible to foresee all the potential situations an agent may encounter and specify an agent behaviour optimally in advance. Agents therefore have to learn from, and adapt to, their environment, especially in a multi-agent setting.

A Framework Based on Multi-agent Systems for Information Retrieval Through Mobile Devices

2005 ◽  
pp. 240-241 ◽  
Author(s):  
Angela Carrillo Ramos ◽  
Jérôme Gensel ◽  
Marlène Villanova-Oliver ◽  
Hervé Martin
Keyword(s):  
Information Retrieval ◽  
Mobile Devices ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

Design of an Intelligent System to Support Tutors in Learning Communities Using Multi-Agent Systems and Fuzzy Logic

2015 ◽  
Vol 10 (8) ◽  
pp. 845 ◽  
Author(s):  
Youness Chaabi ◽  
R. Messoussi ◽  
V. Hilaire ◽  
Y. Ruichek ◽  
K. Lekdioui ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Learning Communities ◽  
Intelligent System ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent
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