Ulrike Hahn

German Inflection: Single Route or Dual Route?

The German plural system has recently become a focal point for conflicting theories of language, both linguistic and cognitive. Marcus et al. (1995) highlight the German plural as support for the dual-route account of inflectional morphology first proposed by Pinker and colleagues (Pinker & Prince, 1988). On the dual-route account, inflectional morphology is universally subserved by a symbolic rule route which deals with regular inflection and an associative memory component which deals with irregular inflection. This contrasts with single-route connectionist systems. We seek to counter supposed evidence for the dual-route account through large-scale simulations as well as through experimental data. We argue that, in its current form, the dual-route account is incapable of generating experimental data provided by Marcus et al. (1995) as support. Finally, we provide direct quantitative comparisons between single-route and dual-route models of German plural inflection and find single-route performance superior on these tests.

Evaluating science arguments: Evidence, uncertainty, and argument strength.

Public debates about socioscientific issues are increasingly prevalent, but the public response to messages about, for example, climate change, does not always seem to match the seriousness of the problem identified by scientists. Is there anything unique about appeals based on scientific evidence-do people evaluate science and nonscience arguments differently? In an attempt to apply a systematic framework to peoples evaluation of science arguments, the authors draw on the Bayesian approach to informal argumentation. The Bayesian approach permits questions about how people evaluate science arguments to be posed and comparisons to be made between the evaluation of science and nonscience arguments. In an experiment involving three separate argument evaluation tasks, the authors investigated whether peoples evaluations of science and nonscience arguments differed in any meaningful way. Although some differences were observed in the relative strength of science and nonscience arguments, the evaluation of science arguments was determined by the same factors as nonscience arguments. Our results suggest that science communicators wishing to construct a successful appeal can make use of the Bayesian framework to distinguish strong and weak arguments.

Effects of category diversity on learning, memory, and generalization

In this study, we examined the effect of within-category diversity on people’s ability to learn perceptual categories, their inclination to generalize categories to novel items, and their ability to distinguish new items from old. After learning to distinguish a control category from an experimental category that was either clustered or diverse, participants performed a test of category generalization or old-new recognition. Diversity made learning more difficult, increased generalization to novel items outside the range of training items, and made it difficult to distinguish such novel items from familiar ones. Regression analyses using the generalized context model suggested that the results could be explained in terms of similarities between old and new items combined with a rescaling of the similarity space that varied according to the diversity of the training items. Participants who learned the diverse category were less sensitive to psychological distance than were the participants who learned a more clustered category.

Bayesian models of cognition

There has been a recent explosion in research applying Bayesian models to cognitive phenomena. This development has resulted from the realization that across a wide variety of tasks the fundamental problem the cognitive system confronts is coping with uncertainty. From visual scene recognition to on-line language comprehension, from categorizing stimuli to determining to what degree an argument is convincing, people must deal with the incompleteness of the information they possess to perform these tasks, many of which have important survival-related consequences. This paper provides a review of Bayesian models of cognition, dividing them up by the different aspects of cognition to which they have been applied. The paper begins with a brief review of Bayesian inference. This falls short of a full technical introduction but the reader is referred to the relevant literature for further details. There follows reviews of Bayesian models in Perception, Categorization, Learning and Causality, Language Processing, Inductive Reasoning, Deductive Reasoning, and Argumentation. In all these areas, it is argued that sophisticated Bayesian models are enhancing our understanding of the underlying cognitive computations involved. It is concluded that a major challenge is to extend the evidential basis for these models, especially to accounts of higher level cognition. WIREs Cogn Sci 2010 1 811-823 For further resources related to this article, please visit the WIREs website.

Induction, deduction, and argument strength in human reasoning and argumentation

Book synopsis: Inductive reasoning is everyday, intuitive reasoning; it contrasts with deductive or logical reasoning. Inductive reasoning is much more prevalent than deductive reasoning, yet there has been much less research on inductive reasoning. Using contributions from the leading researchers in the field, the interdisciplinary approach of this book is relevant to those interested in psychology (including cognitive and developmental psychology), decision-making, philosophy, computer science, and education.

Understanding Similarity: A Joint Project for Psychology,Case-Based Reasoning, and Law

Case-based Reasoning (CBR) began as a theory of human cognition, but has attracted relatively little direct experimental or theoretical investigation in psychology. However, psychologists have developed a range of instance-based theories of cognition and have extensively studied how similarity to past cases can guide categorization of new cases. This paper considers the relation between CBR and psychological research, focussing on similarity in human and artificial case-based reasoning in law. We argue that CBR, psychology and legal theory have complementary contributions to understanding similarity, and describe what each offers. This allows us to establish criteria for assessing existing CBR systems in law and to establish what we consider to be the crucial goals for further research on similarity, both from a psychological and a CBR perspective.

Perceptuo-motor, cognitive, and description-based decision-making seem equally good

Significance Human decision-making seems fundamentally domain dependent. Sensory-motor decisions (e.g., where to put your feet on a rocky ridge) seem near-optimal, whereas decisions based on numerical information (e.g., choosing between financial options) seem suboptimal. Additionally, when people rely on information gained through experience, they make choices that are often the opposite of those they make when relying on described information. However, comparing results across domains on the basis of past results is difficult, because decision-making is studied very differently in different domains. We compared decision-making performance across domains under precisely matched conditions, finding evidence against the idea that fundamental dissociations exist. In fact, peoples’ ability to make decisions seem rather good, although not perfect, in both sensory-motor and cognitive domains. Classical studies suggest that high-level cognitive decisions (e.g., choosing between financial options) are suboptimal. In contrast, low-level decisions (e.g., choosing where to put your feet on a rocky ridge) appear near-optimal: the perception–cognition gap. Moreover, in classical tasks, people appear to put too much weight on unlikely events. In contrast, when people can learn through experience, they appear to put too little weight on unlikely events: the description–experience gap. We eliminated confounding factors and, contrary to what is commonly believed, found results suggesting that (i) the perception–cognition gap is illusory and due to differences in the way performance is assessed; (ii) the description–experience gap arises from the assumption that objective probabilities match subjective ones; (iii) people’s ability to make decisions is better than the classical literature suggests; and (iv) differences between decision-makers are more important for predicting peoples’ choices than differences between choice tasks.

What makes words sound similar

Although similarity plays an important role in accounts of language processing, there are surprisingly few direct empirical studies of the phonological similarity between words, and it is therefore not clear whether similarity comparisons between words involve processes similar to those involved in other cognitive domains. In five experiments, participants chose which of two monosyllabic pseudo-words sounded more similar to a target pseudo-word. Our results are generally consistent with the structural alignment theory of comparisons between complex mental representations, suggesting that phonological word similarity parallels similarity involving other kinds of information including visual objects and scenes, events, and word meanings. We use our results to test new metrics of word similarity, and identify predictions for future similarity research both in the domain of word sounds and in other cognitive domains.

Applying the value of equality unequally: effects of value instantiations that vary in typicality.

Across 4 experiments, the authors investigated the role of value instantiation in bridging the gap between abstract social values and behavior in specific situations. They predicted and found that participants engaged in more egalitarian behavior (point allocation using the minimal group paradigm) after contemplating a typical instantiation of the value of equality compared to an atypical instantiation or a control condition that simply made the value salient. This effect occurred when participants generated reasons for valuing equality in the instantiation (Experiment 1) and when participants merely read about hypothetical examples of the instantiation context (Experiments 2, 3, and 4). Results across experiments indicated that the effect of prior instantiations was not mediated by changes in the abstract value; instead, the process of applying the abstract value was crucial (Experiment 4). Together, the experiments show that the process of applying an abstract value to a specific situation can be influenced by seemingly unrelated prior episodes.

What Does It Mean to be Biased: Motivated Reasoning and Rationality

Abstract In this chapter, we provide a historical overview of research on bias in human cognition, ranging from early work in psychology through the detailed, quantitative examinations of belief revision in the 1960s, the Heuristic and Biases program initiated by Kahneman and Tversky, and bias focused research in personality and social psychology. Different notions of “bias” are identified and compared with the notion of bias in statistics, machine learning, and signal detection theory. Comparison with normative models then forms the basis for a critical look at the evidence that people succumb to motivated reasoning aimed at enabling them “to believe what they want to believe.”