scholarly journals Personalized Intelligent Training on the Web: A Multi-Agent Approach

2002 ◽  
pp. 125-145
Author(s):  
Nicola Capuano ◽  
Massimo De Santo ◽  
Marco Marsella ◽  
Mario Molinara ◽  
Saverio Salerno
Keyword(s):  
Multi Agent ◽  
The Web

Techniques to Improve Multi-Agent Systems for Searching and Mining the Web

2005 ◽  
pp. 463-486 ◽  
Author(s):  
E. Herrera-Viedma ◽  
C. Porcel ◽  
F. Herrera ◽  
L. Martínez ◽  
A.G. Lopez-Herrera
Keyword(s):  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
The Web

SWAMI

2009 ◽  
Vol 4 (3) ◽  
pp. 1-24
Author(s):  
Mark Kilfoil ◽  
Ali Ghorbani
Keyword(s):  
World Wide ◽  
Preliminary Evaluation ◽  
Multi Agent System ◽  
End User ◽  
Look Ahead ◽  
The World ◽  
Multi Agent ◽  
Active Nature ◽  
Intelligent Tools ◽  
The Web

The rapid growth of the World Wide Web has complicated the process of Web browsing by providing an overwhelming wealth of choices for the end user. To alleviate this burden, intelligent tools can do much of the drudge-work of looking ahead, searching and performing a preliminary evaluation of the end pages on the user’s behalf, anticipating the user’s needs and providing the user with more information with which to make fewer, more informed decisions. However, to accomplish this task, the tools need some form of representation of the interests of the user. This article describes the SWAMI system: SWAMI stands for Searching the Web with Agents having Mobility and Intelligence. SWAMI is a prototype that uses a multi-agent system to represent the interests of a user dynamically, and take advantage of the active nature of agents to provide a platform for look-ahead evaluation, page searching, and link swapping. The collection of agents is organized hierarchically according to the apparent interests of the user, which are discovered on-the-fly through multistage clustering. Results from initial testing show that such a system is able to follow the multiple changing interests of a user accurately, and that it is capable of acting fruitfully on these interests to provide a user with useful navigational suggestions.

Applying Information Gathering Techniques in Business-to-Consumer and Web Scenarios

2011 ◽  
pp. 91-112
Author(s):  
David Camacho
Keyword(s):  
Computer Science ◽  
Information Gathering ◽  
Business Community ◽  
Multi Agent System ◽  
Important Research ◽  
Agent Based ◽  
Research Fields ◽  
Multi Agent ◽  
Business To Consumer ◽  
The Web

The last decade has shown the e-business community and computer science researchers that there can be serious problems and pitfalls when e-companies are created. One of the problems is related to the necessity for the management of knowledge (data, information, or other electronic resources) from different companies. This chapter will focus on two important research fields that are currently working to solve this problem — Information Gathering (IG) techniques and Web-enabled Agent technologies. IG techniques are related to the problem of retrieval, extraction and integration of data from different (usually heterogeneous) sources into new forms. Agent and Multi-Agent technologies have been successfully applied in domains such as the Web. This chapter will show, using a specific IG Multi-Agent system called MAPWeb, how information gathering techniques have been successfully combined with agent technologies to build new Web agent-based systems. These systems can be migrated into Business-to-

Applying Information Gathering Techniques in Business-to-Consumer and Web Scenarios

2009 ◽  
pp. 781-799
Author(s):  
David Camacho
Keyword(s):  
Semantic Web ◽  
Computer Science ◽  
Information Gathering ◽  
Business Community ◽  
Important Research ◽  
Agent Based ◽  
Research Fields ◽  
Multi Agent ◽  
Business To Consumer ◽  
The Web

The last decade has shown the e-business community and computer science researchers that there can be serious problems and pitfalls when e-companies are created. One of the problems is related to the necessity for the management of knowledge (data, information, or other electronic resources) from different companies. This chapter will focus on two important research fields that are currently working to solve this problem — Information Gathering (IG) techniques and Web-enabled Agent technologies. IG techniques are related to the problem of retrieval, extraction and integration of data from different (usually heterogeneous) sources into new forms. Agent and Multi-Agent technologies have been successfully applied in domains such as the Web. This chapter will show, using a specific IG Multi-Agent system called MAPWeb, how information gathering techniques have been successfully combined with agent technologies to build new Web agent-based systems. These systems can be migrated into Business- to-Consumer (B2C) scenarios using several technologies related to the Semantic Web, such as SOAP, UDDI or Web services.

scholarly journals Adaptive Interaction Multi-agent Systems in E-learning/E-teaching on the Web

2003 ◽  
pp. 144-153 ◽  
Author(s):  
Antonio Fernández-Caballero ◽  
Victor López-Jaquero ◽  
Francisco Montero ◽  
Pascual González
Keyword(s):  
Multi Agent Systems ◽  
Agent Systems ◽  
E Learning ◽  
Multi Agent ◽  
Adaptive Interaction ◽  
The Web

MARVIN, multi-agent softbot to retrieve multilingual medical information on the Web

1998 ◽  
Vol 23 (3) ◽  
pp. 187-191 ◽  
Author(s):  
O. Baujard ◽  
V. Baujard ◽  
S. Aurel ◽  
C. Boyer ◽  
R. D. Appel
Keyword(s):  
Medical Information ◽  
Multi Agent ◽  
The Web

scholarly journals DAMN: Defeasible Reasoning Tool for Multi-Agent Reasoning

2020 ◽  
Vol 34 (09) ◽  
pp. 13612-13613
Author(s):  
Abdelraouf Hecham ◽  
Madalina Croitoru ◽  
Pierre Bisquert
Keyword(s):  
Decision Making ◽  
Knowledge Base ◽  
Defeasible Reasoning ◽  
Agent Collaboration ◽  
Multi Agent ◽  
The Web

This demonstration paper introduces DAMN: a defeasible reasoning platform available on the web. It is geared towards decision making where each agent has its own knowledge base that can be combined with other agents to detect and visualize conflicts and potentially solve them using a semantics. It allows the use of different defeasible reasoning semantics (ambiguity blocking/propagating with or without team defeat) and integrates agent collaboration and visualization features.

SWAMI

2011 ◽  
pp. 171-195
Author(s):  
Mark Kilfoil ◽  
Ali Ghorbani
Keyword(s):  
World Wide ◽  
Preliminary Evaluation ◽  
End User ◽  
Multi Stage ◽  
Look Ahead ◽  
The World ◽  
Multi Agent ◽  
Active Nature ◽  
Intelligent Tools ◽  
The Web

The rapid growth of the World Wide Web has complicated the process of Web browsing by providing an overwhelming wealth of choices for the end user. To alleviate this burden, intelligent tools can do much of the drudge-work of looking ahead, searching and performing a preliminary evaluation of the end pages on the user’s behalf, anticipating the user’s needs and providing the user with more information with which to make fewer, more informed decisions. However, to accomplish this task, the tools need some form of representation of the interests of the user. This article describes the SWAMI system: SWAMI stands for Searching the Web with Agents having Mobility and Intelligence. SWAMI is a prototype that uses a multi-agent system to represent the interests of a user dynamically, and take advantage of the active nature of agents to provide a platform for look-ahead evaluation, page searching, and link swapping. The collection of agents is organized hierarchically according to the apparent interests of the user, which are discovered on-the-fly through multi-stage clustering. Results from initial testing show that such a system is able to follow the multiple changing interests of a user accurately, and that it is capable of acting fruitfully on these interests to provide a user with useful navigational suggestions.

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