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Test question modulates cue competition between causes and between effects
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The research reported in this article replicated the well-established phenomenon of competition between causes (C) as well as the more controversial presence and absence of competition between effects (E). The test question was identified as a crucial factor leading to each outcome. Competition between causes was obtained when the test question asked about the probability of E given C, p(E/C), implicitly compared with the probability of E given some alternative cause, p(E/C'). competition between effects was obtained when the test question asked about p(C/E) implicitly compared with p(C/E'). Under these conditions, effects competed for diagnostic value just as causes competed for predictive value. Additionally, some conditions in which neither causes nor effects competed were identified. These results suggest a bidirectional and noncompetitive learning process, the contents of which can be used in different ways (competitively or noncompetitively and forward or backward) as a function of test demands.
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... Some findings that are difficult to explain from the associative perspective are, for instance, the effect of the wording of test questions (Collins & Shanks, 2006;Crocker, 1982;Matute, Arcediano, & Miller, 1996;Shou & Smithson, 2015) and the frequency with which judgments are requested (Collins & Shanks, 2002;Matute, Vegas, & De Marez, 2002). These variables have been found to modulate contingency judgments. ...
... In this section, we also discuss some additional problematic phenomena, as well as the explanations that have been proposed to account for them, both from outside and from within the associative stance. For instance, the effect of the wording of test question could be explained from the associative perspective if we assume that different questions tap different associations (e.g., Matute et al., 1996). Similarly, the effect of the frequency of judgments could be understood as a contextual switch, which could explain these results associatively (Vadillo, Vegas, & Matute, 2004). ...
... This result challenges the assumptions of associative theories (that is, sensitivity to this manipulation seems to be another error of omission), though it is also true that several variables were confounded in Waldmann and Holyoak's (1992) experiments, and therefore it was impossible to know which one was actually responsible for the observed effects (see, e.g., Matute et al., 1996;Shanks & López, 1996). For example, in a subsequent experiment, Arcediano, Matute, Escobar, and Miller (2005) separated the effect of several variables that had often been confounded in this research area: directionality of training (predictive vs. diagnostic), directionality of testing (predictive vs. diagnostic), causal status of competing effects (causes or effects), and temporal order of competing stimuli (antecedent events vs. subsequent events) relative to the noncompeting stimuli. ...
Many experiments have shown that humans and other animals can detect contingency between events accurately. This learning is used to make predictions and to infer causal relationships, both of which are critical for survival. Under certain conditions, however, people tend to overestimate a null contingency. We argue that a successful theory of contingency learning should explain both results. The main purpose of the present review is to assess whether cue-outcome associations might provide the common underlying mechanism that would allow us to explain both accurate and biased contingency learning. In addition, we discuss whether associations can also account for causal learning. After providing a brief description on both accurate and biased contingency judgments, we elaborate on the main predictions of associative models and describe some supporting evidence. Then, we discuss a number of findings in the literature that, although conducted with a different purpose and in different areas of research, can also be regarded as supportive of the associative framework. Finally, we discuss some problems with the associative view and discuss some alternative proposals as well as some of the areas of current debate. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
... For example, one study found that causal model effects were only evident when the relevance of the causal structure was specifically emphasised to participants (Lopez, Cobos and Caño, 2005). Matute, Arcediano and Miller (1996) found that the wording of the test question was a critical factor. Asymmetry in cue competition was observed using causality based questions, but not using predictive or diagnostic value questions (which showed competition in both groups), or contiguity questions (which failed to show competition in either group). ...
... While prior studies have shown that causal model-effects depend on the nature of the test question (e.g. Matute et al., 1996), it is not yet known whether the format of the test is important, when the nature of the test question is held constant. Other cue competition effects, like highlighting and the inverse base-rate effect (Medin & Edelson, 1988;Kruschke, 1996;Don & Livesey, 2017) rely almost exclusively on discrete choice test measures and negation test trials. ...
... Sensitivity to causal model manipulations has classically been interpreted as evidence that blocking and other cue competition effects are a result of reasoning at test rather than deficits in learning a connection between the cue and the outcome. For instance, the explanation favored by Matute et al. (1996) is that the blocked and control cues are learned about equally well, and participants use this information flexibly in the test phase, such that different test conditions influence the observation of cue competition effects. For example, participants may remember the outcome that was paired with a particular cue, but may give a lower rating if they infer that the cue does not cause the outcome. ...
Cue competition effects in human contingency learning appear to be sensitive to the causal nature of cue-outcome relationships. While blocking effects are reliably demonstrated in scenarios where cues are presented as causes of outcomes, several studies have failed to find blocking in scenarios where cues are presented as effects of outcomes, a finding that is typically taken as evidence for the involvement of controlled reasoning processes in cue competition. These studies typically measure blocking with continuous causal ratings about individual cues. Previous studies have found that sensitivity to causal model may depend on how the test question is phrased. In contrast, the current study tested the sensitivity of blocking to causal scenarios across different formats of the same test question. Participants completed a causal learning task with instructions suggesting either a predictive (i.e. cue causes outcome) or diagnostic (cue is caused by outcome) cue-outcome relationship. Participants were then asked about the likelihood of outcomes occurring by either giving a continuous rating of each outcome or a discrete choice about the most likely outcome. When measured by continuous ratings of individual cues, blocking was evident in predictive, but not diagnostic scenarios. However, when measured by discrete choice or using a compound negation test, blocking was robust and insensitive to causal scenario. The results suggest that contributions of predictive memory and causal reasoning to cue competition effects may depend substantially on the type of measure used.
... In particular, they dismissed the most problematic result for associative learning theories, namely, the absence of blocking in the diagnostic condition of Experiment 3 (Waldmann & Holyoak, 1992) after diagnostic learning and diagnostic test questions. Matute et al. (1996) suspected that this finding might not be replicable. Some proponents of the associative view argued that lack of statistical power may have prevented the small observed descriptive difference between the ratings of the predictive and the redundant cue (i.e., the blocking effect) from becoming statistically significant (Matute et al., 1996;Shanks & Lopez, 1996). ...
... Matute et al. (1996) suspected that this finding might not be replicable. Some proponents of the associative view argued that lack of statistical power may have prevented the small observed descriptive difference between the ratings of the predictive and the redundant cue (i.e., the blocking effect) from becoming statistically significant (Matute et al., 1996;Shanks & Lopez, 1996). These critiques downplay what, according to Waldmann and Holyoak (1992), was the most important result: a highly reliable interaction between the causal status of the cues and blocking. ...
... These critiques downplay what, according to Waldmann and Holyoak (1992), was the most important result: a highly reliable interaction between the causal status of the cues and blocking. In addition, the generality and validity of the findings were called into question (Matute et al., 1996;Shanks & Lopez, 1996), and it was suggested that the two-phase blocking paradigm used might favor nonassociative types of learning (Price & Yates, 1995). Finally, Waldmann and Holyoak's assumption that prior knowledge caused participants in their Experiment 2 to give low diagnostic ratings to an effect that suggests alternative causes (being underweight) was sometimes misinterpreted or ignored, which opened up the possibility of viewing the obtained low ratings of the redundant cue as evidence for blocking and the results of Experiment 3 (in which prior knowledge was excluded) as a mere failure to replicate (Matute et al., 1996;Miller & Matute, 1998). ...
Causal asymmetry is one of the most fundamental features of the physical world: Causes produce effects, but not vice versa. This article is part of a debate between the view that, in principle, people are sensitive to causal directionality during learning (causal-model theory) and the view that learning primarily involves acquiring associations between cues and outcomes irrespective of their causal role (associative theories). Four experiments are presented that use asymmetries of cue competition to discriminate between these views. These experiments show that, contrary to associative accounts, cue competition interacts with causal status and that people are capable of differentiating between predictive and diagnostic inferences. Additional implications of causal-model theory are elaborated and empirically tested against alternative accounts. The results uniformly favor causal-model theory.
... For example, Bullock, Gelman, & Baillargeon (1982) have argued that humans are predisposed to acquire causal relations between events in their environment even at a young infant age. More recently, Waldmann (e.g., 2000) has argued that humans are predisposed to learn causal relations in a cause-to-effect direction, and that this direction cannot be reversed (but there are multiple detractors of this view; see e.g., López et al., 1998;Matute, Arcediano, & Miller, 1996). ...
... Cell 1-type interference has been observed in blocking (e.g., Arcediano, Matute, & Miller, 1997;Arcediano, Escobar, & Matute, 2001) and overshadowing (e.g., Price & Yates, 1993). Cell 2-type interference has been observed in selected occasions (e.g., Matute, Arcediano, & Miller, 1996;Shanks & López, 1996; but see e.g., Waldmann, 2000;Waldmann & Holyoak, 1992). Cell 3-and Cell 4-type interference has been extensively reported in the human verbal learning tradition (for reviews, see e.g., Britt, 1935;Slamecka & Ceraso, 1960;Swenson, 1941), and more recently in the human causality learning literature (e.g., Escobar, Pineño, & Matute, 2002). ...
... For instance, perhaps judgments that feel more naturally intuitive or familiar to the individual allow a greater influence of associative predictions, particularly among individuals who are disposed to making intuitive judgments already (Livesey et al., 2013). Support for such an influence of non-associative knowledge may be found in studies by Matute et al. (1996), Vadillo et al. (2005) and Vadillo and Matute (2007), which showed that the precise wording of the test question does have an influence on judgements. For example, Matute et al. (1996) found that the relative-validity effect, another cue competition effect related to blocking, appears when subjects are asked to rate whether the target cue X is a cause or an indicator of the outcome, but vanishes when participants are asked to rate to what extent cue X and the outcome co-occurred. ...
... Support for such an influence of non-associative knowledge may be found in studies by Matute et al. (1996), Vadillo et al. (2005) and Vadillo and Matute (2007), which showed that the precise wording of the test question does have an influence on judgements. For example, Matute et al. (1996) found that the relative-validity effect, another cue competition effect related to blocking, appears when subjects are asked to rate whether the target cue X is a cause or an indicator of the outcome, but vanishes when participants are asked to rate to what extent cue X and the outcome co-occurred. Similarly, Gredebäck et al. (2000) found a significant cue competition effect when participants were asked about the predictive value of the cue, as well as when they were asked about the causal relationship between the cue and the outcome. ...
Associative learning theories offer one account of the way animals and humans assess the relationship between events and adapt their behavior according to resulting expectations. They assume knowledge about event relations is represented in associative networks, which consist of mental representations of cues and outcomes and the associative links that connect them. However, in human causal and contingency learning, many researchers have found that variance in standard learning effects is controlled by “non-associative” factors that are not easily captured by associative models. This has given rise to accounts of learning based on higher-order cognitive processes, some of which reject altogether the notion that humans learn in the manner described by associative networks. Despite the renewed focus on this debate in recent years, few efforts have been made to consider how the operations of associative networks and other cognitive operations could potentially interact in the course of learning. This paper thus explores possible ways in which non-associative knowledge may affect associative learning processes: (1) via changes to stimulus representations, (2) via changes to the translation of the associative expectation into behavior (3) via a shared source of expectation of the outcome that is sensitive to both the strength of associative retrieval and evaluation from non-associative influences.
... For example, Matute, Arcediano, and Miller (1996) reported that the manner in which the test question was worded strongly influenced the results that were obtained. ...
p>It has long been known that the impairment to discrimination learning caused by brief delays to reinforcement can be counteracted by the response-contingent presentation of a conditioned reinforcer during the delay interval following a correct response (Spence, 1947). More recently, it has been shown that reinforcement delay can also be overcome using response-marking procedures, in which the same stimulus contingently follows both correct responses and errors (e.g. Lieberman, McIntosh & Thomas, 1979). This thesis examined the effects of response-marking procedures on human learning of conditional discrimination tasks with delayed reinforcement.
Experiments One to Three employed single case experimental designs (alternating treatments) to evaluate the effect of response marking during matching-to-sample tasks with delayed reinforcement, using children with autism as participants. Experiment One showed that for both marking and conditioned reinforcement supported acquisition of conditional discrimination performance over a 5 s delay, although the latter appeared more efficient. Experiment Two, however, showed that – with more effective techniques – both procedures were equally effective, and that both were more effective than a control in which no response-contingent stimuli occurred during the delay. Experiment Three compared the standard marking procedure with a novel marked-before procedure in which all sample stimuli were marked before a matching response was made. Both procedures produced very similar acquisition rates, and both were more effective in establishing conditional discrimination than a delay only control.
Experiments four to Seven employed group comparison designs to compare marking against conditioned reinforcement, delay and immediate reinforcement using adult humans in a laboratory version of the matching-to-sample task. Marking effects were found only in Experiment Seven, when the confounding effects of verbal behaviour were adequately controlled.
Overall, the findings indicated that response-marking procedures may be effective with human participants but that their effects are more reliable in applied settings with children than in laboratory settings with adults.</p
... When predictions later have to Associative Learning 43 be made about cues, only exemplar-based processing is available. In fact, several authors have failed to find cue interaction when people are asked to make judgments about cues (e.g., Matute, Arcediano, & Miller, 1996;Waldmann & Holyoak, 1992). Another factor might be the ambiguity of outcome information. ...
... It predicted the outcome no better than the camouflage. When participants were asked to judge the contingency between the camouflage and the tank exploding, participants from the condition where the plane was no better at predicting the explosion ranked the contingency as higher than in the condition where the plane was the better predictor (see also Matute, Arcediano, & Miller, 1996). ...
Select literature regarding cue competition, the contents of learning, and retrieval processes is summarized to demonstrate parallels and differences between human and nonhuman associative learning. Competition phenomena such as blocking, overshadowing, and relative predictive validity are largely analogous in animal and human learning. In general, strong parallels are found in the associative structures established during learning, as well as in the basic phenomena associated with information retrieval. Some differences arise too, such as retrospective evaluation, which seems easier to observe in human than in nonhuman animals. However, the parallels are sufficient to indicate that the study of learning in animals continues to be relevant to human learning and memory.
This research studies the relationship between figure and ground, which is a concept introduced by Gestalt theory. There has been much research done in
capturing a figure image against a background and used in applications such as artificial image perception. However, little has been done to understand their
relationship. For our investigation we studied double image illusion, which allows us to analyze images with more than one figure-ground interpretation. Rough set derived lattices are introduced to reflect the differing figure-ground contrasts. The two types of indiscernibilities of rough set theory let us consider the two different interpretations of double image illusions. The resulting logical structures are considerably original for those generated by such images.
Research on causal reasoning has focused on the influence of covariation between candidate causes and effects on causal judgments. We suggest that the type of covariation information to which people attend is affected by the task being performed. For this, we manipulated the test questions for the evaluation of contingency information and observed its influence on both contingency learning and subsequent causal selections. When people select one cause related to an effect, they focus on conditional contingencies assuming the absence of alternative causes. When people select two causes related to an effect, they focus on conditional contingencies assuming the presence of alternative causes. We demonstrated this use of contingency information in four experiments.
Shanks (1991) reported experiments that show selective-learning effects in a categorization task, and presented simulations of his data using a connectionist network model implementing the Rescorla-Wagner (R-W) theory of animal conditioning. He concluded that his results (a) support the application of the R-W theory to account for human categorization, and (b) contradict a particular variant of contingency-based theories of categorization. We examine these conclusions. We show that the asymptotic weights produced by the R-W model actually predict systematic deviations from the observed human learning data. Shanks claimed that his simulations provided good qualitative fits to the observed data when the weights in the networks were allowed to reach their asymptotic values. However, analytic derivations of the asymptotic weights reveal that the final weights obtained in Shanks' Simulations 1 and 2 do not correspond to the actual asymptotic weights, apparently because the networks were not in fact run to asymptote. We show that a contingency-based theory that incorporates the notion of focal sets can provide a more adequate explanation of cue competition than does the R-W model.
Five conditioned lick-suppression experiments with water-deprived rats examined the possibility that simultaneous and backward associations are learned, but are not expressed as anticipatory responses in common indexes of associative strength. Experiments 1–4 used a sensory preconditioning procedure in which clicks preceded the onset of a tone. Subsequently, the tone was paired with footshock in either a forward, simultaneous, or backward arrangement. In no case did the tone trained in the simultaneous or backward manner elicit a conditioned response. However, Experiments 1, 2, and 3 determined that the clicks, which predicted the tone, evoked equally strong conditioned responses regardless of whether the tone was paired with the shock in a forward, simultaneous, or backward manner. Experiment 4 found that responding to the clicks was degraded following postconditioning extinction of the tone, regardless of whether the tone had been paired with the shock in a forward or simultaneous manner. Experiment 5 determined that if the click and tone were paired simultaneously, the click failed a test for excitation following tone-shock simultaneous pairings but passed a test for excitation following tone-shock forward pairings. Collectively, these findings suggest that predictive information (i.e., a forward relationship between stimuli) is not necessary for the acquisition of an association, but may promote the expression of the association in an anticipatory response system. Moreover, these results suggest that associations are not simple linkages, but contain information regarding the temporal relationship of the associates.
Ciiven the task of di the source of a patient's aUer^'ic reav-tion. college students jiuigcii the causal efficacy of common (A') and distinctive (A and Bj elements of compound stimuli: AX and BX. As the differential correlation of AX and BX with the occurrence and nonoccurrence ofthe allergic reaction rose from .00 to 1.00. ratings of ihe distinctive A and B elements diverged; most importantly, ratings ofthe common X element fell. These causal judgments of humans closely parallel the conditioned responses of animals in associa-tive learning studies, and clearly disclose that stimuli compete with one another for control over behavior.
Melz, Cheng, Holyoak, and Waldmann (1993) argue that the partial blocking of cue A that I reported (Shanks, 1991a) when subjects were presented with intermixed AB → 1, B → 1 category learning trials is not consistent with the associative Rescorla and Wagner (1972) theory analysis that I offered, given that the theory predicts complete blocking at asymptote. However, this claim assumes that subjects' were trained to asymptote in my experiments, and there is no reason to believe this was the case. Melz et al.'s further argument that there has been no reported evidence of complete blocking in associative learning tasks is incorrect. I show that, on the contrary, there is abundant evidence of it. The Rescorla and Wagner theory analysis of my results is therefore sound. The results I reported were inconsistent with contingency theories as they are normally formulated. Melz et al. propose a revised contingency theory which, they argue, can account for data from a range of learning tasks. In particular, Melz et al. claim that their theory can accommodate my results. I show that the theory can be refuted on the following grounds: (a) It is contradicted by a wealth of data from other associative learning experiments, (b) it does not in fact account for the data I obtained, and (c) for many situations in which the Rescorla and Wagner theory makes clear testable predictions, the revised contingency theory is either undefined and hence makes no predictions, or else has so many degrees of freedom that it can essentially predict any result that might be obtained.
Three experiments tested a simple connectionist network approach to human categorization. The specific network considered consists of a layer of input nodes, each representing a feature of the exemplar to be categorized, connected in parallel to a layer of output nodes representing the categories. Learning to categorize exemplars consists of adjusting the weights in the network so as to increase the probability of making correct categorizations; weight changes are determined by the Rescorla-Wagner (1972) learning rule. The experiments used a simulated medical diagnosis procedure in which subjects have to decide which disease (the category) each of a series of patients is suffering from on the basis of the patients' symptoms (the features). After a series of trials, the subjects rated the extent to which particular symptoms were associated with particular diseases. In each of the experiments, it is shown that a process of selective learning occurs in this categorization task and that selection in turn depends on the relative predictiveness of the symptom for the disease. Such effects parallel results found in animal conditioning experiments and are readily reproduced by the connectionist network model. The results are also discussed in terms of a variety of traditional theories of categorization.
This chapter describes the potential explanatory power of a specific response rule and its implications for models of acquisition. This response rule is called the “comparator hypothesis.” It was originally inspired by Rescorla's contingency theory. Rescorla noted that if the number and frequency of conditioned stimulus–unconditioned stimulus (CS–US) pairings are held constant, unsignaled presentations of the US during training attenuate conditioned responding. This observation complemented the long recognized fact that the delivery of nonreinforced presentations of the CS during training also attenuates conditioned responding. The symmetry of the two findings prompted Rescorla to propose that during training, subjects inferred both the probability of the US in the presence of the CS and the probability of the US in the absence of the CS and they then established a CS–US association based upon a comparison of these quantities. The comparator hypothesis is a qualitative response rule, which, in principle, can complement any model of acquisition.
In three experiments we investigated the effect on the performance of thirsty rats of varying the instrumental contingency between lever pressing and the delivery of a saccharin reinforcer. In Experiment 1, the subjects performed more slowly in a non-contingent condition, in which the momentary probability of reinforcement was unaffected by whether or not the animals pressed, than in a contingent condition in which the reinforcer was never presented except following a lever press. This was true of performance under both random ratio and interval schedules in which the function determining the probability of reinforcement following a lever press remained the same across the contingent and non-contingent conditions. Experiment 2 demonstrated that instrumental performance was less affected when the contingency was degraded by the introduction of free reinforcers if these reinforcers were signalled. In Experiment 3, lever pressing was reinstated to some degree after non-contingent training by giving non-reinforced exposure to the operant chamber in the absence of the lever. These results suggest that free reinforcers depress instrumental behaviour through a performance mechanism engaged by their ability to support conditioning of the contextual cues.
The possibility of reversing the deficit produced by overshadowing through the use of memory reactivation was investigated. Using lick suppression as a measure of associative strength, water-deprived rats were conditioned in a Pavlovian paradigm which produced reliable overshadowing of a flashing light by a tone. It was found, however, that exposure to the overshadowed stimulus outside of the conditioning context during the retention interval (reminder treatment) caused an increase in lick suppression during testing in animals that had undergone overshadowing, relative to nonreminded overshadowed animals. Subjects that received the reminder treatment but were conditioned without overshadowing showed no increase in lick suppression. Additional control groups ensured that the increase in suppression observed in the overshadowed subjects following reminder treatment was not due to nonspecific fear. The results suggest that the performance deficit produced by overshadowing is due at least in part to a reversible failure to efficiently retrieve associations to the overshadowed stimulus at the time of testing, rather than a failure to form those associations during conditioning.