Cognitive architectures have often been applied to data from individual experiments. In this paper, I develop an ACT-R reader that can model a much larger set of data, eye-tracking corpus data. It is shown that the resulting model has a good fit to the data for the considered low-level processes. Unlike previous related works, the model achieves the fit by estimating free parameters of ACT-R using Bayesian estimation and Markov-Chain Monte Carlo techniques, rather than by relying on the mix of (...) manual selection + default values. The method used in the paper is generalizable beyond this particular model and data set and could be used on other ACT-R models. (shrink)

Modified numerals, such as at least three and more than five, are known to sometimes give rise to ignorance inferences. However, there is disagreement in the literature regarding the nature of these inferences, their context dependence, and differences between at least and more than. We present a series of experiments which sheds new light on these issues. Our results show that the ignorance inferences of at least are more robust than those of more than, the presence and strength of the (...) ignorance inferences triggered by both at least and more than depends on the question under discussion, and whether ignorance inferences are detected in a given experimental setting depends partly on the task that participants are asked to perform. We offer an Optimality Theoretic account of these findings. In particular, the task effect is captured by assuming that in performing an acceptability task, participants take the speaker’s perspective in order to determine whether an expression is optimal given a certain epistemic state, while in performing an inference task they take the addressee’s perspective in order to determine what the most likely epistemic state of the speaker is given a certain expression. To execute the latter task in a fully rational manner, participants have to perform higher-order reasoning about alternative expressions the speaker could have used. Under the assumption that participants do not always perform such higher-order reasoning but also often resort to so-called unidirectional optimization, the task effect finds a natural explanation. This also allows us to relate our finding to asymmetries between comprehension and production that have been found in language acquisition. (shrink)

Quantifiers in phrasal and clausal comparatives often seem to take distributive scope in the matrix clause: for instance, the sentence John is taller than every girl is is true iff for every girl it holds that John is taller than that girl. Broadly speaking, two approaches exist that derive this reading without postulating the wide scope of the quantifier: the negation analysis and the interval analysis of than-clauses. We propose a modification of the interval analysis in which than-clauses are not (...) treated as degree intervals but as degree pluralities. This small change has significant consequences: it yields a straightforward account of differentials in comparatives and it correctly predicts the existence of hitherto unnoticed readings, viz. cumulative readings of clausal comparatives. Finally, this paper also makes the case that using degree pluralities is conceptually appealing: it allows us to restrict the analysis of comparatives by mechanisms that are postulated independently in the semantics of pluralities. (shrink)

This paper develops a novel psycholinguistic parser and tests it against experimental and corpus reading data. The parser builds on the recent research into memory structures, which argues that memory retrieval is content‐addressable and cue‐based. It is shown that the theory of cue‐based memory systems can be combined with transition‐based parsing to produce a parser that, when combined with the cognitive architecture ACT‐R, can model reading and predict online behavioral measures (reading times and regressions). The parser's modeling capacities are tested (...) against self‐paced reading experimental data (Grodner & Gibson, 2005), eye‐tracking experimental data (Staub, 2011), and a self‐paced reading corpus (Futrell et al., 2018). (shrink)

This squib reports the results of two experimental studies, a binary choice and a self-paced reading study, that provide strong support for the hypothesis in Tunstall that the distinct scopal properties of each and every are at least to some extent the consequence of an event-differentiation requirement contributed by each. However, we also show that the emerging picture is more complex than Tunstall suggests: English speakers seem to fall into at least three groups regarding the scopal properties of each and (...) every. (shrink)

We investigate how Reinforcement Learning methods can be used to solve the production selection and production ordering problem in ACT‐R. We focus on four algorithms from the Q learning family, tabular Q and three versions of Deep Q Networks, as well as the ACT‐R utility learning algorithm, which provides a baseline for the Q algorithms. We compare the performance of these five algorithms in a range of lexical decision tasks framed as sequential decision problems.