Conditional Inference and Activation of Knowledge Entities in ACT-R (2110.15214v1)

Abstract: Activation-based conditional inference applies conditional reasoning to ACT-R, a cognitive architecture developed to formalize human reasoning. The idea of activation-based conditional inference is to determine a reasonable subset of a conditional belief base in order to draw inductive inferences in time. Central to activation-based conditional inference is the activation function which assigns to the conditionals in the belief base a degree of activation mainly based on the conditional's relevance for the current query and its usage history. Therewith, our approach integrates several aspects of human reasoning into expert systems such as focusing, forgetting, and remembering.