Neural networks: Studying their decision-making rules

Neural networks for soft decision making

This paper discusses various techniques for soft decision making by neural networks. Decision making problems are described as choosing an action from possible alternatives using available information. In the context of soft decision making, a single action is not always chosen. When it is di cult to choose a single action based on available information, the decision is withheld or a set of pro...

Statistical Decision Making and Neural Networks

NeuroLinear: From neural networks to oblique decision rules

We present NeuroLinear, a system for extracting oblique decision rules from neural networks that have been trained for classiication of patterns. Each condition of an oblique decision rule corresponds to a partition of the attribute space by a hyperplane that is not necessarily axis-parallel. Allowing a set of such hyperplanes to form the boundaries of the decision regions leads to a signiicant...

Studying Group Decision Making in Affinity Diagramming

Affinity diagramming is a commonly used contextual design practice for which many tools have been developed. However, experts and novices alike eschew tool use, instead using traditional paper and whiteboard methods. This paper presents observations of traditional affinity diagramming sessions, focusing on three areas of consideration—shared awareness, cognitive offloading, and understanding, o...

Variants of uncertainty in decision-making and their neural correlates.

When leaving the tidy world of rules and people start judging probabilities on an intuitive basis, it revealed that they have some intuitions to choose from. One could refer to them as a family of subjective probability concepts or following Kahneman and Tversky, as variants of uncertainty. The authors distinguished between external and internal attributions of uncertainty and could show that t...