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3.3 The agent’s architecture
Orlando Belo
To be able to support all the most common services required by a typical process for bibliographic
references suggestion, we designed the agent’s architecture (Figure 3) organized into three functional
layers with the following components:
Layer 1 – Interface
User Interface, which provides sensors and actuators to establish and maintain communication
between the agent and the students.
Information Retrieval, with the special task to retrieve document’s sources from the Web and
make their full indexation.
Layer 2 – Reasoning
Reasoning, which receives the user requests, evaluating them and generating suggestion about
some bibliographic references, taking into consideration the student’s preferences (if already
defined) and the importance level attributed by the lecturing team.
Acquaintance, a component that keeps information about other assistant agents (application area,
expertise and knowledge, references lists and application domains, etc.) working in the same
platform.
Monitoring and Control, which observes and records all user requests and their reference lists
selection for later user profiling and preferences evaluation.
Layer 3 – Knowledge and Data Access
Working Memory, which keeps intermediate results and control parameters.
Knowledge Base, a knowledge repository that keeps all the data objects and their relation ships
about bibliographic references and their relation with the topics of the course’s programme – see
a brief example in Figure 3.
This agent software was conceived to work as a complementary tutoring component that can be
integrated in an eLearning platform, acting accordingly its directives and communicate with other
services. The model proposed in this paper will allow the implementation of an assistant agent that
would reduce lecturing teams efforts and time wasted in the explanation and presentation of
bibliographic resources. At the same time will provide an entity permanently available and that can be
access almost everywhere if we have access to it. It was also considered the integration of several
assistant agents in the same platform, in order to ensure access to different bibliographic resources
and promote agent cooperation in cases of bibliographic cross-referencing.
4. Conclusions and future work
Today, eLearning platforms are introduced in almost teaching institutions. From a partial fulfilling of
some specific oriented services to a global integration in all aspects of teaching, eLearning tools
perform very important roles in learning processes, providing tutoring and supporting services
permanently, and with easy access for the entire student (and teaching) community. In this work we
were concerned with only a specific aspect of tutoring: bibliographic suggestion; with the simple
objective to help and support university students improving their learning outcomes. The option by an
agent application was related to the intrinsic characteristics of any agent-based applications:
autonomy, adaptation and cooperation. The proposed model followed the characteristics of the most
common agent-based systems, differing essentially in how the agent will acquire and maintain its
knowledge, and extend its application context. The rest of the components are quite regular, as well
as the global behaviour of the agent.
According to the most basic characteristics of the architecture proposed for the implementation of a
personal assistant for bibliographic resources suggestions, we intend to implement the assistant
agent as soon as possible, following the FIPA (The Foundation for Intelligent Physical Agents -
http://www.fipa.org/) specifications, which provides us a set of well know standards for agent-based
services and inter-agent communication. Additionally, to ensure a well-structured and robust platform
for agents we will use the JADE platform (Bellifemine et al. 2008), a generic software for agent-based
applications, which provides the most basic functionalities required by software agents (asynchronous
messages, agent life cycle management, mechanisms for agent subscription, ontology support, etc.).
Jade supports all the major FIPA’s specifications and will allow us to develop rapidly the software for
the bibliographic assistant.
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