The Use of Agents Techniques on Intelligent Tutoring Systems

In recent years, the term agent has been incorporated to the vocabulary of mainstream Computer Science (CS), used to name from simple system process to highly skilled software/hardware resembles, denoting an entity created to perform either a specific task or set of tasks. Such a wide notion is straighten in Artificial Intelligence (AI), where researchers are interested in a notion that confers to the agent the property of being intelligent. This tendency occurs also in case of Intelligent Tutoring Systems (ITS) and in Intelligent Learning Environments (ILE) when we can consider agents as Pedagogical Agents. We can have different types of Pedagogical Agents: Tutor, Mentor, Assistance, MOO, Web (agents working on INTERNET applications), Learner’s agents and mixed agents (which can teach and learn). Pedagogical agents have a set of normative teaching goals and plans for achieving these goals (e.g., teaching strategies), and associated resources in the learning environment [34]. Tutoring agents are entities whose ultimate purpose is to communicate with the student in order to efficiently fulfil their respective tutoring function, as part of the pedagogical mission of the system [19]. So, educational applications, in general, are based on Tutor and Mentor agents. Even on WEB applications, where the focus is on distance learning [17; 18; 23; 24; 26]. There is no consensual definition about agents on AI field. Researchers from connected areas (like education and psychology) interested in have knowledge about it will find the concepts sprayed on very technical reports and papers just into AI meetings or specific