Affiliations: ICAR – Istituto di calcolo e reti ad alte
prestazioni, Sezione di Palermo – Italian National Research Council, Viale
delle Scienze, 90128 Palermo, Italy. E-mail: {g.pilato,
s.vitabile}@icar.cnr.it | DINFO – Dipartimento di ingegneria informatica –
University of Palermo, Viale delle Scienze, 90128 Palermo, Italy. E-mail:
[email protected], {gvassallo, sorbello}@unipa.it
Abstract: A neural based multi-agent system, exploiting the Web Directories as
a Knowledge Base for information sharing and documents retrieval, is presented.
The system is based on the EαNet architecture, a neural network capable
of learning the activation function of its hidden units and having good
generalization capabilities. System goal is to retrieve, among documents shared
by a networked community, documents satisfying a query and dealing with a
specific topic. The system is composed by four agents: the Trainer Agent, the
Neural Classifier Agent, the Interface Agent, and the Librarian Agent. The
sub-symbolic knowledge of the Neural Classifier Agent is automatically updated
each time a new, not included before, document topic is requested by users. The
system is very efficient: the experimental results show that, in the best case,
a classification error about 10% is obtained.
