Norms are useful tools to regulate autonomous agents, and their generality is the focus of this paper. The norms refers extent behaviors capable regulating. While very specific tend be inefficient avoid undesirable (since they rarely activated), general limit excessively options agents activated too often) hindering them achieve system goal. Therefore, a norm that efficiently regulates should h...

During knowledge acquisition multiple alternative potential rules all appear equally credible. This paper addresses the dearth of formal analysis about how to select between such alternatives. It presents two hypotheses about the expected impact of selecting between classification rules of differing levels of generality in the absence of other evidence about their likely relative performance on...

Many pattern recognition and machine learning approaches employ a distance metric on patterns, or a generality relation to partially order the patterns. We investigate the relationship amongst them and prove a theorem that shows how a distance metric can be derived from a partial order (and a corresponding size on patterns) under mild conditions. We then discuss the use of the theorem. More spe...