FLAP Journal 2023 Journal Article
Activation-based Conditional Inference.
- Marco Wilhelm
- Diana Howey
- Gabriele Kern-Isberner
- Kai Sauerwald
- Christoph Beierle
Activation-based conditional inference (ActInf) combines conditional rea- soning and ACT-R, a cognitive architecture developed to formalize human rea- soning, and therewith provides a powerful inference formalism which makes it possible to integrate several aspects of human reasoning, such as focusing, forgetting, and remembering, into formal uncertain reasoning. The basic idea of activation-based conditional inference is to determine a reasonable, cogni- tively adequate subset of a conditional belief base before drawing inductive inferences. Central to activation-based conditional inference is the activation function which assigns to the conditionals in the belief base a degree of acti- vation mainly based on the conditional’s relevance for the current query and its usage history. Here, we develop a blueprint for activation-based conditional inference and illustrate how focusing, forgetting, and remembering are included within our framework.