Autonomous robots must be able to learn and maintain models of their environments.
Research on mobile robot navigation has produced two major paradigms for mapping …

A structured organization of information is typically required by symbolic processing. On the
other hand, most connectionist models assume that data are organized according to …

To date, the preponderance of techniques for eliciting the knowledge embedded in trained
artificial neural networks (ANN's) has focused primarily on extracting rule-based …

Connectionist research is firmly established within the scientific community, especially within
the multi-disciplinary field of cognitive science. This diversity, however, has created an …

There has been an increased interest in combining fuzzy systems with neural networks
because fuzzy neural systems merge the advantages of both paradigms. On the one hand …

We introduce a model for analog computation with discrete time in the presence of analog
noise that is flexible enough to cover the most important concrete cases, such as noisy …

In August 1998 Dave Touretzky asked on the connectionists e-mailing list,\Is connectionist
symbol processing dead?" This query lead to an interesting discussion and exchange of …

In the paper we address the problem of computation in recurrent neural networks (RNN). In
the first part we provide a formal analysis of the dynamical behavior of a RNN with a single …

A simple extension of standard neural network models is introduced which provides a model
for neural computations that involve both firing rates and firing correlations. Such an …

We consider the problem of learning a finite automaton with recurrent neural networks from
positive evidence. We train an Elman recurrent neural network with a set of sentences in a …