Ignore similarity if you can: a computational exploration of exemplar similarity effects on rule application

It is generally assumed that when making categorization judgments the cognitive system learns to focus on stimuli features that are relevant for making an accurate judgment. This is a key feature of hybrid categorization systems, which selectively weight the use of exemplar- and rule-based processes. In contrast, Hahn et al. (2010) have shown that people cannot help but pay attention to exemplar similarity, even when doing so leads to classification errors. This paper tests, through a series of computer simulations, whether a hybrid categorization model developed in the ACT-R cognitive architecture (by Anderson and Betz, 2001) can account for the Hahn et al. dataset. This model implements Nosofsky and Palmeri’s (1997) exemplar-based random walk model as its exemplar route, and combines it with an implementation of Nosofsky et al. (1994) rule-based model RULEX. A thorough search of the model’s parameter space showed that while the presence of an exemplar-similarity effect on response times was associated with classification errors it was possible to fit both measures to the observed data for an unsupervised version of the task (i.e., in which no feedback on accuracy was given). Difficulties arose when the model was applied to a supervised version of the task in which explicit feedback on accuracy was given. Modeling results show that the exemplar-similarity effect is diminished by feedback as the model learns to avoid the error-prone exemplar-route, taking instead the accurate rule-route. In contrast to the model, Hahn et al. found that people continue to exhibit robust exemplar-similarity effects even when given feedback. This work highlights a challenge for understanding how and why people combine rules and exemplars when making categorization decisions

Klösterliche Grundherrschaftsverwaltung in Südwestdeutschland : Der Kellhof von Sankt Blasien in Blumberg-Fützen

Form und Ausstattung des Hauses von 1689 (d) lassen eine ehemals herrschaftliche Funktion vermuten. Diese konnte anhand von Quellen belegt werden. Repräsentationsanspruch und Verwaltungsaufgaben sind bis heute unmittelbar ablesbar

We might be wrong, but we think that hedging doesn't protect your reputation.

We gain much of our knowledge from other people. Since people are fallible - they lie, mislead, and are mistaken - it seems essential to monitor their claims and their reliability as sources of information. An intuitive way to do this is to draw on our expectations about claims and sources: to perform expectation-based updating (Hahn, Merdes, & von Sydow, 2018). But this updating can have damaging consequences, leading us into a kind of confirmation bias. An alternative is to keep track of outcomes and record whether a claim proves true or false: to perform outcome-based updating (Hahn et al., 2018). This form of updating does not have the negative repercussions on belief accuracy. But both forms of updating might undermine the trust and cooperation assumed to be necessary for successful communication. We explore a potential boundary condition on these types of updating. We investigate whether speakers can protect their reputation when they make claims with low prior probability, with and without knowledge of the final outcome. We explore suggestions from McCready (2015) that speakers can protect themselves by hedging with evidential language: in particular with weaker propositional attitudes ('I suspect that...') and so-called double hedges ('I might be wrong, but I think...'). We find that both forms of updating are robust to hedging with this evidential language, and find no clear evidence for a protective effect. We discuss extra ingredients that may allow successful hedging

Conditionals, Individual Variation, and the Scorekeeping Task

In this manuscript we study individual variation in the interpretation of conditionals by establishing individual profiles of the participants based on their behavioral responses and reflective attitudes. To investigate the participants’ reflective attitudes we introduce a new experimental paradigm called the Scorekeeping Task, and a Bayesian mixture model tailored to analyze the data. The goal is thereby to identify the participants who follow the Suppositional Theory of conditionals and Inferentialism and to investigate their performance on the uncertain and-to-if inference task

Who “Believes” in the Gambler’s Fallacy and why?

Humans possess a remarkable ability to discriminate structure from randomness in the environment. However, this ability appears to be systematically biased. This is nowhere more evident than in the Gambler’s Fallacy (GF) – the mistaken belief that observing an increasingly long sequence of ‘heads’ from an unbiased coin makes the occurrence of ‘tails’ on the next trial ever more likely. Although the GF appears to provide evidence of ‘cognitive bias’, a recent theoretical account (Hahn & Warren, 2009) has suggested the GF might be understandable if constraints on actual experience of random sources (such as attention and short term memory) are taken into account. Here we test this experiential account by exposing participants to 200 outcomes from a genuinely random (p=.5) Bernoulli process. All participants saw the same overall sequence; however, we manipulated experience across groups such that the sequence was divided into chunks of length 100, 10 or 5. Both before and after the exposure, participants i) generated random sequences and ii) judged the randomness of presented sequences. In contrast to other accounts in the literature, the experiential account suggests that this manipulation will lead to systematic differences in post-exposure behaviour. Our data were strongly in line with this prediction and provide support for a general account of randomness perception in which biases are actually apt reflections of environmental statistics under experiential constraints. This suggests that deeper insight into human cognition may be gained if, instead of dismissing apparent biases as failings, we assume humans are rational under constraints

Similarity and structured representation in human and nonhuman apes

How we judge the similarity between objects in the world is connected ultimately to how we represent those objects. It has been argued extensively that object representations in humans are ‘structured’ in nature, meaning that both individual features and the relations between them can influence similarity. In contrast, popular models within comparative psychology assume that nonhuman species appreciate only surface-level, featural similarities. By applying psychological models of structural and featural similarity (from conjunctive feature models to Tversky's contrast model) to visual similarity judgements from adult humans, chimpanzees, and gorillas, we demonstrate a cross-species sensitivity to complex structural information, particularly for stimuli that combine colour and shape. These results shed new light on the representational complexity of nonhuman apes, and the fundamental limits of featural coding in explaining object representation and similarity, which emerge strikingly across both human and nonhuman species

The impact of partial source dependence on belief and reliability revision

In this paper, we explore how people revise their belief in a hypothesis and the reliability of sources in circumstances where those sources are either independent or are partially dependent because of their shared, common, background. Specifically, we examine people’s revision of perceived source reliability by comparison with a formal model of reliability revision proposed by Bovens and Hartmann (2003). This model predicts a u-shaped trajectory for revision in certain circumstances: If a source provides a positive report for an unlikely hypothesis, perceived source reliability should decrease; as additional positive reports emerge, however, estimates of reliability should increase. Participants’ updates in our experiment show this u-shaped pattern. Furthermore, participants’ responses also respect a second feature of the model, namely that perceived reliability should once again decrease when it becomes known that the sources are partially dependent. Participants revise appropriately both when a specific shared reliability is observed (e.g. sources went to the same, low quality school) and when integrating the possibility of shared reliability. These findings shed light on how people gauge source reliability and integrate reports when multiple sources weigh in on an issue as seen in public debates

On the ignorance of group-level effects – The tragedy of personnel evaluation?

In social-dilemma situations (e.g., public-good games), people may pursue their local self- interests, thereby lowering the overall payoff of their group and, paradoxically, even their individual payoffs as a result. Likewise, in inner-individual dilemmas, even without conflict of interest between persons, people may pursue local goals at the expense of overall utility. Our experiments investigate such dissociations of individual and group-level effects in the context of personnel evaluation and selection. Participants were given the role of human resource managers selecting workers to optimize the overall payoff for the company. We investigated contexts where the individually best/worst ‘employees’ systematically caused the worst/best group performance. When workers in a team could substantially increase or decrease co-workers’ performance, most participants (albeit not all) tended to focus solely on individual performance without considering their overall contribution even when instructed to maximize group performance. This undue focus on individual information meant that employees who enhanced team performance the most often received the most negative evaluations. This may result in a ‘tragedy of personnel evaluation’ relevant to maladaptive incentive structures (personnel evaluation), job offers (personnel selection), and a substantially negative impact on organizational effectiveness. At the same time, the results suggest ways this problem may be overcome

Is this what the debate on rules was about? Commentary on Pothos, E.

The key weakness of the proposed distinction between rules and similarity is that it effectively converts what was previously seen as a consequence of rule or similarity-based processing, into a definition of rule and similarity themselves – evidence is elevated into a conceptual distinction. This conflicts with fundamental intuitions about processes and erodes the relevance of the debate across cognitive science

Argument quality in Real-World Argumentation

The idea of resolving dispute through the exchange of arguments and reasons has been central to society for millennia. We exchange arguments as a way of getting at the truth in contexts as diverse as science, the court room, and our everyday lives. In democracies, political decisions should be negotiated through argument, not deception, or even worse, brute force. If argument is to lead to the truth or to good decisions, then some arguments must be better than others and ‘argument strength’ must have some meaningful connection with truth. Can argument strength be measured in a way that tracks an objective relationship with truth, and not just mere persuasiveness? This article describes recent developments in providing such measures