Abstract

Some inferences are seemingly automatic (reflexive; Shastri & Ajjanagadde, 1993), whereas others require more effort (i.e., are reflective). We present the beginnings of an integrated account of reflexive and reflective reasoning, based on the LISA model of analogical reasoning (Hummel & Holyoak, 1997). The account holds that reflexive inferences are those that can be generated automatically based on existing knowledge in long-term memory, whereas reflective inferences require explicit structuremapping and therefore demand greater attention and working memory. According to this account, reflexive inferences manifest themselves in the semantic encoding of objects and predicates, whereas reflective inferences manifest themselves as explicit propositions. In contrast to reflexive inferences, which are equally reflexive, reflective inferences may require more or less effort. We present preliminary simulation results demonstrating that both kinds of inference can be modeled in a single architecture for representing propositional knowledge.

Citations