Throughout its brief history, the field of artificial intelligence (Ai) has been the arena of jousts
between two freres ennemis, symbolicism and connectionism. No sooner had …

A variety of ideas, approaches, and techniques exist--in terms of both architecture and
learning--and this abundance seems to lead to many exciting possibilities in terms of …

Labeled graphs are an appropriate and popular representation of structured objects in many
domains. If the labels describe the properties of real world objects and their relations, finding …

This paper looks at the representation of supra-classical, non-monotonic (SCNM) logic by an
artificial neural network. It identifies the features of defeasiblity in this logic related to …

The present study is an account of human motivational phenomena from a functional
contextualistic perspective with the specific goal of improving prediction and influence in the …

2 Architectures and Techniques for Knowledge- Based Neurocomputing Page 1 The
knowledge-data trade-off in machine learning reflects the fact that most learning takes place …

Throughout its brief history, the eld of arti cial intelligence (ai) has been the arena of jousts
between two fr eres ennemis, symbolicism and connectionism. No sooner had …

Labeled graphs are an appropriate and popular representation of structured objects in many
domains. If the labels describe the properties of real world objects and their relations, nding …

Fully-connected binary networks, in addition to implementing content addressable
memories, have been shown to be capable of encoding arbitrary limit cycles using …

This dissertation presents a unified methodology for encoding structural and functional
knowledge using stochastic Petri nets. Petri nets are an established tool for representing …