Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
There is increasing evidence to suggest that the neocortex of the mammalian brain does not consist of a collection of specialised and dedicated cortical architectures, but instead ...
John Thornton, Torbjorn Gustafsson, Michael Blumen...
In this paper we present some aspects of an intelligent interface for a WWWeb legal information retrieval system. Our system is able to keep the context of the user interaction in...
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
In this paper, we focus on lexical semantics, a key issue in Natural Language Processing (NLP) that tends to converge with conceptual Knowledge Representation (KR) and ontologies....