  Cognitive theories for reasoning are about understanding how humans come to
conclusions from a set of premises. Starting from hypothetical thoughts, we are
interested which are the implications behind basic everyday language and how do
we reason with them. A widely studied topic is whether cognitive theories can
account for typical reasoning tasks and be confirmed by own empirical
experiments. This paper takes a different view and we do not propose a theory,
but instead take findings from the literature and show how these, formalized as
cognitive principles within a logical framework, can establish a quantitative
notion of reasoning, which we call plausibility. For this purpose, we employ
techniques from non-monotonic reasoning and computer science, namely, a solving
paradigm called answer set programming (ASP). Finally, we can fruitfully use
plausibility reasoning in ASP to test the effects of an existing experiment and
explain different majority responses.
