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One of Mackintosh's many contributions to the comparative psychology of associative learning was in developing the distinction between the mental processes responsible for learning about features and learning about relations. His research on discrimination learning and generalisation served to highlight differences and commonalities in learning mechanisms across species and paradigms. In one such example, Wills and Mackintosh trained both pigeons and humans to discriminate between two categories of complex patterns comprising overlapping sets of abstract visual features. They demonstrated that pigeons and humans produced similar "peak-shifted" generalisation gradients when the proportion of shared features was systemically varied across a set of transfer stimuli, providing support for an elemental feature-based analysis of discrimination and generalisation. Here, we report a series of experiments inspired by this work, investigating the processes involved in post-discrimination generalisation in human category learning. We investigate how post-discrimination generalisation is affected by variability in the spatial arrangement and probability of occurrence of the visual features and develop an associative learning model that builds on Mackintosh's theoretical approach to elemental associative learning. [ABSTRACT FROM AUTHOR]

When a cue reliably predicts an outcome, the associability of that cue will change. Associative theories of learning propose this change will persist even when the same cue is paired with a different outcome. These theories, however, do not extend the same privilege to an outcome; an outcome's learning history is deemed to have no bearing on subsequent new learning involving that outcome. Two experiments were conducted which sought to investigate this assumption inherent in these theories using a serial letter-prediction task. In both experiments, participants were exposed, in Stage 1, to a predictable outcome ('X') and an unpredictable outcome ('Z'). In Stage 2, participants were exposed to the same outcomes preceded by novel cues which were equally predictive of both outcomes. Both experiments revealed that participants' learning towards the previously predictable outcome was more rapid in Stage 2 than the previously unpredicted outcome. The implications of these results for theories of associative learning are discussed. [ABSTRACT FROM AUTHOR]

Most associative models typically assume that learning can be understood as a gradual change in associative strength that captures the situation into one single parameter, or representational state. We will call this view single-state learning. However, there is ample evidence showing that under many circumstances different relationships that share features can be learned independently, and animals can quickly switch between expressing one or another. We will call this multiple-state learning. Theoretically, it is understudied because it needs a different data analysis approach from those usually employed. In this article, we present a Bayesian model of the Partial Reinforcement Extinction Effect (PREE) that can test the predictions of the multiple-state view. This implies estimating the moment of change in the responses (from the acquisition to the extinction performance), both at the individual and group levels. We used this model to analyze data from a PREE experiment with three levels of reinforcement during acquisition (100%, 75% and 50%). We found differences in the estimated moment of switch between states during extinction, so that it was delayed after leaner partial reinforcement schedules. The finding is compatible with the multiple-state view. It is the first time, to our knowledge, that the predictions from the multiple-state view are tested directly. The article also aims to show the benefits that Bayesian methods can bring to the associative learning field. [ABSTRACT FROM AUTHOR]

An experiment with rats compared the ability of fixed and variable duration cues to produce blocking. Rats in group B (Blocking) were trained that both fixed- (F) and variable- (V) duration cues would be followed by food delivery. In a subsequent training stageFandVcontinued to be reinforced, butFwas accompanied byX, andVbyY. In the test phase responding toXandYwas examined. Control group O (Overshadowing) received identical treatment, except thatFandVwere nonreinforced in the first training stage. In group B there was evidence for blocking, but only ofX,which had been conditioned in compound with the fixed-durationF; there was no evidence for blocking ofY, which had been conditioned in compound with the variable-durationV. It is suggested that this result may occur because fixed cues reach a higher, more stable asymptote of associative strength than do their variable equivalents. [ABSTRACT FROM PUBLISHER]

Prior research has suggested that attention is determined by exploiting what is known about the most valid predictors of outcomes and exploring those stimuli that are associated with the greatest degree of uncertainty about subsequent events. Previous studies of human contingency learning have revealed evidence for one or other of these processes, but differences in the designs and procedures of these studies make it difficult to pinpoint the crucial determinant of whether attentional exploitation or exploration will dominate. Here we present two studies in which we systematically manipulated both the predictiveness of cues and uncertainty regarding the outcomes with which they were associated. This allowed us to demonstrate, for the first time, evidence of both attentional exploration and exploitation within the same experiment. Moreover, while the effect of predictiveness persisted to influence the rate of novel learning about the same cues in a second stage, the effect of uncertainty did not. This suggests that attentional exploration is more sensitive to a change of context than is exploitation. The pattern of data is simulated with a hybrid attentional model. [ABSTRACT FROM PUBLISHER]

Determinants of a positive patterning advantage (that is, an advantage for positive patterning over negative patterning) in human causal reasoning were examined in an experiment that compared simple patterning discriminations (A, B vs. AB) to complex patterning discriminations (AB, BC, AC vs. ABC). As predicted by a cue constellation analysis of complex discriminations, a positive patterning advantage was found with complex patterning but not with simple patterning discriminations. This result may explain why some recent studies have found a positive patterning advantage where earlier studies had failed to find one. The interaction of patterning complexity with the positive patterning advantage appears to pose problems for rule-based accounts of patterning. The results support the view that associative theories of human causal reasoning are more easily distinguished from rule-based approaches when applied to conditions that make simple rules difficult to identify or implement. [ABSTRACT FROM PUBLISHER]

The acquisition of a negative evaluation of a fictitious minority social group in spite of the absence of any objective correlation between group membership and negative behaviours was described by Hamilton and Gifford (1976) as an instance of an illusory correlation. We studied the acquisition and attenuation through time of this correlation learning effect. In two experiments we asked for participants' judgements of two fictitious groups using an online version of a group membership belief paradigm. We tested how judgements of the two groups changed as a function of the amount of training they received. Results suggest that the perception of the illusory correlation effect is initially absent, emerges with intermediate amounts of absolute experience, but diminishes and is eliminated with increased experience. This illusory correlation effect can be considered to reflect incomplete learning rather than a bias due to information loss in judgements or distinctiveness. [ABSTRACT FROM AUTHOR]