UCLA

Human thinking relies on the ability to process relations between individuals, kinds, properties, and other relations. Explicit relation processing has been invoked to explain our ability to grasp ‘cross-domain’ analogies between situations whose similarity is driven by a shared relational structure, rather than any similarities among the relata populating each analog (e.g., between the solar system and an atom) and ‘cross-modal’ analogies between relata spanning different sensory modalities (e.g., sound and vision); generalize relational schemas, categories whose members share some canonical structure (e.g., things consisting of elements converging on a central location); or abstract rule-like sequences (e.g., an A-B-A sequence of syllables). At the same time, explicit relation processing requires that a reasoner simultaneously represent a set of individual relata and then bind them to a relational structure. This ability is slow to develop in childhood, and even among adults, it places high demands on working memory. Relations thus raise a tension between the expressive advantage they confer and the cognitive cost they impose, and this tension suggests that the human ability for relation processing does not imply its inevitable use, especially when less-demanding alternatives are available.The present dissertation confronts this tension and attempts to specify the computational mechanisms by which human reasoners process relations in the face of their cognitive demands. It presents novel research that clarifies how humans make use of explicitly relational thought instead of nonrelational alternatives. In Chapter 1, I start by examining the role of relations in comparison. Cognitive scientists researching analogy have generalized the processes governing analogical comparison, and the representations of relational structure that it operates on, to all comparison. A consequence of this view is that human reasoners make use of relations whenever they make any comparison. I test this claim and show that whereas relations do tend to underlie comparisons aimed at assessing similarity, they tend not to underlie assessments of difference. This asymmetry is consistent with recent accounts of a representational asymmetry between the relations same and different, in which different is represented as a negation of the relation same (i.e., different is represented as not-same). When judging difference, human reasoners are more likely to shift to simpler non-relational representations to ease working memory capacity. Having lent support to the claim that explicit similarity judgments do tend to incorporate relational information, I extend this claim to implicit similarity comparisons made during recognition in Chapter 2. When an agent attempts to assess whether they recognize a given stimulus, they make an implicit comparison between the perceptually available stimulus to a representation in memory. I show that when agents make this comparison, they tend to incorporate relational information; indeed, relations are available to serve as cues in human recognition memory. Finally, in Chapter 3, I examine a cognitive process, generative analogical inference, that integrates human reasoning and memory, investigated relatively independently in Chapters 1 and 2 respectively. I introduce a computational model of this process, in which a reasoner uses their prior knowledge of some familiar source domain to elaborate on some less-familiar target domain. This new model can reproduce human-like inference whether the relational structure that constrains inference is prespecified in the model input, as required by existing inference models, or are unspecified, unlike existing models. Across three simulations, I use comparisons between this model and a non-relational control model to clarify what relations contribute to the inference process. Specifically, relations promote far generalization across semantically distance analogs. My dissertation instantiates a framework for studying human relation processing that acknowledges both the expressive advantages that relations provide and the cognitive costs imposed by processing them.