Cultivating intelligent tutoring cognizing agents in ill-defined domains using hybrid approaches

Cognizing agents are those systems that can perceive information from the external environment and can adapt to the changing conditions of that environment. Along the adaptation process a cognizing agent perceives information about the environment and generates reactions. An intelligent tutoring cognizing agent should deal not only with the tutoring system’s world but also with the learner-it should infer and predict new information about the learner and tailor the learning process to fit this specific learner. This paper shows how intelligent tutoring cognizing agents can be cultivated in ill-defined domains using hybrid techniques instantiated in the two example agents AEINS-CA and ALES-CA. These agents offer adaptive learning process and personalized feedback aiming to transfer certain cognitive skills, such as problem solving skills to the learners and develop their reasoning in the two ill-defined domains of ethics and argumentation. The paper focuses on the internal structure of each agent and the reasoning methodology, in which, the cognizing agent administration and construction along with the pedagogical scenarios are described

Towards the measurement of Enterprise Information Systems agility to support EIS improving projects

International audienceEnterprise information systems (EIS) are directly implied in the global performance of an organisation. Nevertheless, their potential rigidity in comparison with the required fast evolution of the supported organisation remains an important open research question. The proposed research work aims to define and evaluate the agility of an EIS, in order to assist both software engineers and business managers in EIS improvement projects. In particular, a framework is proposed to structure the different existing metrics on agility according to the improvements needs and the intrinsic characteristics of an information system