One for All and All in One

Abstract

For the past few years several research teams have been developing intelligent learning environments (ILE) based on multi-agent architectures. For such type of architectures to be possible, the agents must have specific roles in the architecture and must be able to communicate in between them. To handle such needs, we have established a generic multi-agent architecture — the Pedagogical Agents Communication Framework (PACF). In PACF a set of agents were defined, their roles established, and their communication infrastructure built. Such communication infrastructure is based on a subset of the KQML language. There are two main general agents in PACF: the Server that acts both as a facilitator in the KQML sense and as an application-independent name server; and a Learner Modelling Server (LMS). The LMS can be used by several applications (composed by several agents) and each one can adapt the modelling strategy to its needs through the parameterisation of three configuration files: one that provides the application domain structure and the others the learner modelling strategies. Through this parameterisation the applications define how the LMS will model their learners. The LMS keeps one single database for all the learners being modelled by all the agents, allowing different applications to access to the same learner model simultaneously. These different applications can share parts of the learner models provided that they use the same domain ontology in the modelling process. This architecture has been used in a Web based distance learning scenario with two different ILEs.