—This paper details a learning decision-theoretic intelligent agent designed to solve the problem of guiding vehicles in the context of Personal Rapid Transit (PRT). The intellig...
This paper proposes an unsupervised learning model for classifying named entities. This model uses a training set, built automatically by means of a small-scale named entity dicti...
This paper reports on the implication of different preferred learning styles on students'performance in the introductory programming sequence and on work in progress on how t...
Lynda Thomas, Mark Ratcliffe, John Woodbury, Emma ...
Some supervised-learning algorithms can make effective use of domain knowledge in addition to the input-output pairs commonly used in machine learning. However, formulating this a...
It is well known that prior knowledge or bias can speed up learning, at least in theory. It has proved di cult to make constructive use of prior knowledge, so that approximately c...