A central question in online human sentence comprehension is, "How are linguistic relations established between different parts of a sentence?" Previous work has shown that this dependency resolution process can be computationally expensive, but the underlying reasons for this are still unclear. This article argues that dependency resolution is mediated by cue-based retrieval, constrained by independently motivated working memory principles defined in a cognitive architecture. To demonstrate this, this article investigates an unusual instance of dependency resolution, the processing of negative and positive polarity items, and confirms a surprising prediction of the cue-based retrieval model: Partialcue matches-which constitute a kind of similarity-based interference-can give rise to the intrusion of ungrammatical retrieval candidates, leading to both processing slow-downs and even errors of judgment that take the form of illusions of grammaticality in patently ungrammatical structures. A notable achievement is that good quantitative fits are achieved without adjusting the key model parameters.

To effectively wayfind through unfamiliar buildings, humans infer their relative position to target locations not only by interpreting geometric layouts, especially length of line of sight, but also by using background knowledge to evaluate landmarks with respect to their probable spatial relation to a target. Questionnaire results revealed that participants have consistent background knowledge about the relative position of target locations. Landmarks were rated significantly differently with respect to their spatial relation to targets. In addition, results from a forced-choice task comparing snapshots of a virtual environment revealed that background knowledge influenced wayfinding decisions. We suggest that landmarks are interpreted semantically with respect to their function and spatial relation to the target location and thereby influence wayfinding decisions. This indicates that background knowledge plays a role in wayfinding.

Empirical findings indicate that humans draw infer- ences about spatial arrangements by constructing and manipulating mental models which are internal representations of objects and relations in spatial working memory. Central to the Mental Model Theory (MMT), is the assumption that the human reasoning process can be divided into three phases: (i) Mental model construction, (ii) model inspection, and (iii) model validation. The MMT can be formalized with respect to a computational model, connecting the reasoning process to operations on mental model representations. In this respect a computational model has been implemented in the cognitive architecture ACT-R capable of explaining human reasoning difficulty by the number of model operations. The presented ACT-R model allows simulation of psychological findings about spatial reasoning problems from a previous study that investigated conventional behavioral data such as response times and error rates in the context of certain mental model construction principles.

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