Modeling Associative Reasoning Processes
It addresses the long-standing challenge in cognitive science of creating predictive models for human associative reasoning, with potential implications for understanding cognitive phenomena like consciousness.
The paper tackles the problem of modeling associative reasoning processes by proposing a formally sound method that adapts logical reasoning mechanisms, and demonstrates its application to modeling mind-wandering and the Remote Associates Test for creativity.
The human capability to reason about one domain by using knowledge of other domains has been researched for more than 50 years, but models that are formally sound and predict cognitive process are sparse. We propose a formally sound method that models associative reasoning by adapting logical reasoning mechanisms. In particular it is shown that the combination with large commensense knowledge within a single reasoning system demands for an efficient and powerful association technique. This approach is also used for modelling mind-wandering and the Remote Associates Test (RAT) for testing creativity. In a general discussion we show implications of the model for a broad variety of cognitive phenomena including consciousness.