Intelligent tutoring systems founded of incremental dynamic case based reasoning and multi-agent systems (ITS-IDCBR-MAS)

Author(s):  
Abdelhamid Zouhair ◽  
El Mokhtar En-Naimi ◽  
Benaissa Amami ◽  
Hadhoum Boukachour ◽  
Patrick Person ◽  
...  
2007 ◽  
Vol 10 (1) ◽  
Author(s):  
Rosa M. Viccari ◽  
Demetrio A. Ovalle ◽  
Jovani A. Jimenez

This paper presents a description of the environments of individualized learning (Based on the Intelligent Tutoring Systems, ITS), the Computer Supported Collaborative Learning (CSCL), Multi-Agent Systems (MAS) and the artificial intelligence techniques called: Instruc- tional Planning (IP) and Case-Based Reasoning (CBR). Finally ALLEGRO is presented, a MAS environment of support to the teaching/learning process that includes all previous artificial in- telligence elements.


Author(s):  
Carolina González ◽  
Juan Carlos Burguillo ◽  
Martín Llamas ◽  
Rosalía Laza

Intelligent Tutoring Systems (ITSs) are educational systems that use artificial intelligence techniques for representing the knowledge. ITSs design is often criticized for being a complex and challenging process. In this article, we propose a framework for the ITSs design using Case Based Reasoning (CBR) and Multiagent systems (MAS). The major advantage of using CBR is to allow the intelligent system to propose smart and quick solutions to problems, even in complex domains, avoiding the time necessary to derive those solutions from scratch. The use of intelligent agents and MAS architectures supports the retrieval of similar students models and the adaptation of teaching strategies according to the student profile. We describe deeply how the combination of both technologies helps to simplify the design of new ITSs and personalize the e-learning process for each student


2009 ◽  
Vol 24 (4) ◽  
pp. 327-352 ◽  
Author(s):  
Stella Heras ◽  
Vicente Botti ◽  
Vicente Julián

AbstractNowadays, Multi-Agent Systems (MAS) are broadening their applications to open environments, where heterogeneous agents could enter into the system, form agents’ organizations and interact. The high dynamism of open MAS gives rise to potential conflicts between agents and thus, to a need for a mechanism to reach agreements. Argumentation is a natural way of harmonizing conflicts of opinion that has been applied to many disciplines, such as Case-Based Reasoning (CBR) and MAS. Some approaches that apply CBR to manage argumentation in MAS have been proposed in the literature. These improve agents’ argumentation skills by allowing them to reason and learn from experiences. In this paper, we have reviewed these approaches and identified the current contributions of the CBR methodology in this area. As a result of this work, we have proposed several open issues that must be taken into consideration to develop a CBR framework that provides the agents of an open MAS with arguing and learning capabilities.


Sign in / Sign up

Export Citation Format

Share Document