Case base adaptation using solution-space metrics

In this paper we propose a generalisation of the k-nearest neighbour (k-NN) retrieval method based on an error function using distance metrics in the solution and problem space. It is an interpolative method which is proposed to be effective for sparse case bases. The method applies equally to nominal, continuous and mixed domains, and does not depend upon an embedding n-dimensional space. In continuous Euclidean problem domains, the method is shown to be a generalisation of the Shepard's Interpolation method. We term the retrieval algorithm the Generalised Shepard Nearest Neighbour (GSNN) method. A novel aspect of GSNN is that it provides a general method for interpolation over nominal solution domains. The performance of the retrieval method is examined with reference to the Iris classification problem,and to a simulated sparse nominal value test problem. The introducion of a solution-space metric is shown to out-perform conventional nearest neighbours methods on sparse case bases.

Casual link and consensual arrangements in estoppel

Analyses the Court of Appeal decision in Powell v Benney on whether in a claim of proprietary estoppel the expectation of a couple that they would receive two properties owned, and promised to them, by a deceased friend was out of proportion to the detriment suffered by them in looking after the friend and improving his properties for their own use. Considers: (1) the approach to be taken to the requirement of a causal link between the assurance given and the conduct constituting the detriment relied on; and (2) consensual arrangements and estoppel equity.

Making the link: a customised social networking site can foster learning

Thanks to the internet, students today can do things that students of the past could not. They can learn formally or informally by interacting on social networking sites in a way that is not easily accomplished in a lecture theatre or classroom.

The missing link between information and action: hastenings and delays as universal reactions to performance feedback

This chapter focuses on what the key decision makers in organizations decide after having received information on the current state of the organizational performance. Because of strong attributions to success and failure, it is impossible to predict in advance which concrete actions will occur. We can however find out what kinds of actions are decided upon by means of an organizational learning model that focuses on the hastenings and delays after performance feedback. As an illustration, the responses to performance signals by trainers and club owners in Dutch soccer clubs are analyzed.