Complexity in Classificatory Reasoning

Abstract

Classificatory reasoning involves the tasks of concept evaluation and classification, which may be performed with use of the strategies of concept matching and concept activation, respectively. Different implementations of the strategies of concept matching and concept activation are possible, where an implementation is characterized by the organization of knowledge and the control of information processing it uses. In this paper we define the tasks of concept evaluation and classification, and describe the strategies of concept matching and concept activation. We then derive the computational complexity of the tasks using different implementations of the task-specific strategies. We show that the complexity of performing a task is determined by the organization of knowledge used in performing it. Further, we suggest that the implementation that is computationally the most efficient for performing a task may be cognitively the most plausible as well.