Overview of CALEP: a Competency Based Learning Path Generation System

Author(s):  
Meriem Hnida ◽  
Mohammed Khalidi Idrissi ◽  
Samir Bennani
2010 ◽  
Vol 166-167 ◽  
pp. 161-166
Author(s):  
Ionut Dinulescu ◽  
Dorin Popescu ◽  
Mircea Nitulescu ◽  
Alice Predescu

Recent advances in the domains of social and life artificial intelligence have constituted the basis for a new discipline that studies cooperation in multi-robot systems and its utility in applications where some tasks cannot be carried out by a single robot. This paper introduces a trajectory generator which is used for determination of the most appropriate trajectory which a robot needs to track in order to perform different tasks specific to cooperative robots, such as moving in a given formation or pushing an object to a given destination. Different algorithms are described in this paper, starting from simple polyline and circular paths to complex Bezier trajectories. Simulation results of the proposed path generation system are also provided, along with the description of its implementation on real mobile robots. An implementation of real robots is also presented in this paper.


Author(s):  
Mohamed Bendahmane ◽  
Brahim El Falaki ◽  
Mohammed Benattou

In most existing E-learning systems, activities' content and order are presented in a static manner without taking into consideration the learners characteristics, profiles or competencies. The challenge is to adapt and regulate learning processes according to the learner profile by applying learning models that use new information technologies. There are several adaptation approaches of E-learning environments, such as, adaptive hypermedia system, semantic web, etc. In our proposed system, we adopted a Competency Based Approach to offer each learner an individualized learning path for the acquisition of the competence targeted on the basis of the collaborative filtering. Concerning the technological aspect, the system is implemented as a web services while adhering to a service-oriented architecture. This allows interoperability with heterogeneous learning systems


2015 ◽  
Vol 19 (3) ◽  
Author(s):  
Claudia Pérez Martínez ◽  
Gabriel López Morteo ◽  
Magally Martínez Reyes ◽  
Alexander Gelbukh

Author(s):  
Shinya Hibino ◽  
Yukiharu Kodama ◽  
Yasunori Nagasaka ◽  
Tomoichi Takahashi ◽  
Kazuhito Murakami ◽  
...  

Author(s):  
Roberto Pirrone ◽  
Giovanni Pilato ◽  
Riccardo Rizzo ◽  
Giuseppe Russo

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