Learning Defaults: Recognizing Patterns in Beliefs

This paper deals with a “default” learning scheme. The closely related paradigm is learning by observation. As inductive inference forms the basis for the proposed learning scheme, the default generation process acquires nonmonotonic behaviour. This nonmonotonic behaviour is captured by using a formal system with a modified version of the modus ponens as the inference rule. We propose an intuitively-appealing classification of defaults into four categories. The classification is essentially based on specific and general defaults. The formal system, presented in this paper, deals with specific defaults that form the basis for general defaults. We also observe that the bidirectional defaults can be successfully employed in reasoning.