Categorization with a very high missing data rate is seldom studied, especially from a non-probabilistic point of view. This paper proposes a new algorithm called default clusterin...
TIELT is a software testbed that facilitates the integration and testing of learning-embedded decision systems on user-selected tasks from virtual gaming simulators. A key componen...
Reusing past experiences by reasoning from past cases poses particular problems when the input to case retrieval comes from large amounts of online data. Volve has developed a syst...
In this paper, we present a learning framework for the semantic annotation of text documents that can be used as textual cases in case-based reasoning applications. The annotation...
In this paper we present our preliminary investigation of rational agents who can learn from their experience. We claim that such agents need to combine at least three attributes