Design of an Adaptive e-Learning System based on Multi-Agent Approach and Reinforcement Learning

Adaptive e-learning systems are created to facilitate the learning process. These able suggest student most suitable pedagogical strategy and extract information characteristics of learners. A multi-agent system is a collection organized independent agents that communicate with each other resolve problem or complete well-defined objective. always in communication they can be homogeneous heterogeneous may not have common objectives. The application approach adaptive enhance process quality by customizing contents students’ needs. these collaborate provide personalized experience. In this paper, design an adaptative based on reinforcement presented. main objective recommendation students path meets their preferences using Q-learning algorithm. proposed focused three principal characteristics, style according Felder-Silverman model, knowledge level, student's possible disabilities. Three types disabilities were taken into account, namely hearing impairments, visual dyslexia. will sequence objects matches profiles for