PROBabilities from EXemplars (PROBEX): a “lazy” algorithm for probabilistic inference from generic knowledge

PROBEX (PROBabilities from EXemplars), a model of probabilistic inference and probability judgment based on generic knowledge is presented. Its properties are that: (a) it provides an exemplar model satisfying bounded rationality; (b) it is a “lazy” algorithm that presumes no pre‐computed abstractions; (c) it implements a hybrid‐representation, similarity‐graded probability. We investigate the ecological rationality of PROBEX and find that it compares favorably with Take‐The‐Best and multiple regression (Gigerenzer, Todd, & the ABC Research Group, 1999). PROBEX is fitted to the point estimates, decisions, and probability assessments by human participants. The best fit is obtained for a version that weights frequency heavily and retrieves only two exemplars. It is proposed that PROBEX implements speed and frugality in a psychologically plausible way.     

Can the Mind Command the Body?

People naturally intuit that an agent's ethereal thoughts can cause its body to move. Per intuitive physics; however, one body can only interact with another. Are people, then, covertly puzzled by the capacity of thoughts to command the body? Experiment 1 first confirms that thoughts (e.g., thinking about a cup) are indeed perceived as ethereal—as less detectible in the body (brain), and more likely to exist in the afterlife relative to matched percepts (e.g., seeing a cup). Experiments 2–5 show that thoughts are considered less likely to cause behavior than percepts (e.g., thinking of a cup vs. seeing one). Furthermore, mind–body causation is more remarkable when its bodily consequences are salient (e.g., moving an arm vs. brain activation). Finally, epistemic causes are remarkable only when they are ascribed to mental- (e.g., “thinking”) but not to physical states (“activation”). Together, these results suggest that mind–body interactions elicit a latent dualist dissonance.     

Causal Information-Seeking Strategies Change Across Childhood and Adolescence

Intervening on causal systems can illuminate their underlying structures. Past work has shown that, relative to adults, young children often make intervention decisions that appear to confirm a single hypothesis rather than those that optimally discriminate alternative hypotheses. Here, we investigated how the ability to make informative causal interventions changes across development. Ninety participants between the ages of 7 and 25 completed 40 different puzzles in which they had to intervene on various causal systems to determine their underlying structures. Each puzzle comprised a three- or four-node computer chip with hidden wires. On each trial, participants viewed two possible arrangements of the chip's hidden wires and had to select a single node to activate. After observing the outcome of their intervention, participants selected a wire configuration and rated their confidence in their selection. We characterized participant choices with a Bayesian measurement model that indexed the extent to which participants selected nodes that would best disambiguate the two possible causal structures versus those that had high causal centrality in one of the two causal hypotheses but did not necessarily discriminate between them. Our model estimates revealed that the use of a discriminatory strategy increased through early adolescence. Further, developmental improvements in intervention strategy were related to changes in the ability to accurately judge the strength of evidence that interventions revealed, as indexed by participants' confidence in their selections. Our results suggest that improvements in causal information-seeking extend into adolescence and may be driven by metacognitive sensitivity to the efficacy of previous interventions in discriminating competing ideas.     

Emergent Goal-Anticipatory Gaze in Infants via Event-Predictive Learning and Inference

From about 7 months of age onward, infants start to reliably fixate the goal of an observed action, such as a grasp, before the action is complete. The available research has identified a variety of factors that influence such goal-anticipatory gaze shifts, including the experience with the shown action events and familiarity with the observed agents. However, the underlying cognitive processes are still heavily debated. We propose that our minds (i) tend to structure sensorimotor dynamics into probabilistic, generative event-predictive, and event boundary predictive models, and, meanwhile, (ii) choose actions with the objective to minimize predicted uncertainty. We implement this proposition by means of event-predictive learning and active inference. The implemented learning mechanism induces an inductive, event-predictive bias, thus developing schematic encodings of experienced events and event boundaries. The implemented active inference principle chooses actions by aiming at minimizing expected future uncertainty. We train our system on multiple object-manipulation events. As a result, the generation of goal-anticipatory gaze shifts emerges while learning about object manipulations: the model starts fixating the inferred goal already at the start of an observed event after having sampled some experience with possible events and when a familiar agent (i.e., a hand) is involved. Meanwhile, the model keeps reactively tracking an unfamiliar agent (i.e., a mechanical claw) that is performing the same movement. We qualitatively compare these modeling results to behavioral data of infants and conclude that event-predictive learning combined with active inference may be critical for eliciting goal-anticipatory gaze behavior in infants.     

Postselection Inference in Structural Equation Modeling

Abstract

Most statistical inference methods were established under the assumption that the fitted model is known in advance. In practice, however, researchers often obtain their final model by some data-driven selection process. The selection process makes the finally fitted model random, and it also influences the sampling distribution of the estimator. Therefore, implementing naive inference methods may result in wrong conclusions—which is probably a prime source of the reproducibility crisis in psychological science. The present study accommodates three valid state-of-the-art postselection inference methods for structural equation modeling (SEM) from the statistical literature: data splitting (DS), postselection inference (PoSI), and the polyhedral (PH) method. A simulation is conducted to compare the three methods with the commonly used naive procedure under selection events made by L₁-penalized SEM. The results show that the naive method often yields incorrect inference, and that the valid methods control the coverage rate in most cases with their own pros and cons. Real world data examples show the practical use of the valid inference methods.     

Children Change Their Answers in Response to Neutral Follow-Up Questions by a Knowledgeable Asker

Burgeoning evidence suggests that when children observe data, they use knowledge of the demonstrator's intent to augment learning. We propose that the effects of social learning may go beyond cases where children observe data, to cases where they receive no new information at all. We present a model of how simply asking a question a second time may lead to belief revision, when the questioner is expected to know the correct answer. We provide an analysis of the CHILDES corpus to show that these neutral follow-up questions are used in parent–child conversations. We then present three experiments investigating 4- and 5-year-old children's reactions to neutral follow-up questions posed by ignorant or knowledgeable questioners. Children were more likely to change their answers in response to a neutral follow-up question from a knowledgeable questioner than an ignorant one. We discuss the implications of these results in the context of common practices in legal, educational, and experimental psychological settings.     

Visual impressions of active and inanimate resistance to impact from a moving object

ABSTRACT

Images of moving objects presented on computer screens may be perceived as animate or inanimate. A simple hypothesis, consistent with much research evidence, is that objects are perceived as inanimate if there is a visible external contact from another object immediately prior to the onset of motion, and as animate if that is not the case. Evidence is reported that is not consistent with that hypothesis. Objects (targets) moving on contact from another object (launcher) were perceived as actively resisting the impact of the launcher on them if the targets slowed rapidly. Rapid slowing is consistent with the laws of mechanics for objects moving in an environment that offers friction and air resistance. Despite that, ratings of inanimate motion were lower than ratings of active resistance for objects that slowed rapidly. The results are consistent with the hypothesis that there is a perceptual impression of active (animate) resistance that is evoked by the kinematic pattern of rapid slowing from an initial speed after contact from another object.     

Inferring Behavior From Partial Social Information Plays Little or No Role in the Cultural Transmission of Adaptive Traits

Many human cultural traits become increasingly beneficial as they are repeatedly transmitted, thanks to an accumulation of modifications made by successive generations. But how do later generations typically avoid modifications which revert traits to less beneficial forms already sampled and rejected by earlier generations? And how can later generations do so without direct exposure to their predecessors' behavior? One possibility is that learners are sensitive to cues of non-random production in others' behavior, and that particular variants (e.g., those containing structural regularities unlikely to occur spontaneously) have been produced deliberately and with some effort. If this non-random behavior is attributed to an informed strategy, then the learner may infer that apparent avoidance of certain possibilities indicates that these have already been sampled and rejected. This could potentially prevent performance plateaus resulting from learners modifying inherited behaviors randomly. We test this hypothesis in four experiments in which participants, either individually or in interacting dyads, attempt to locate rewards in a search grid, guided by partial information about another individual's experience of the task. We find that in some contexts, valid inferences about another's behavior can be made from partial information, and these inferences can be used in a way which facilitates trait adaptation. However, the benefit of these inferences appears to be limited, and in many contexts—including some which have the potential to make inferring the experience of another individual easier—there appears to be no benefit at all. We suggest that inferring previous behavior from partial social information plays a minimal role in the adaptation of cultural traits.     

Show me the meaning! The contextual relevance of images influences the recall and understanding of multimedia RSVP paragraphs

ABSTRACT

This study examined whether images facilitate contextual grouping as effectively as words. College students (N?=?102) read RSVP paragraphs with topics located at the beginning, middle, or end of the paragraph. Paragraph topic was presented as a topic-related image, topic-unrelated image, or written explicitly in text. Topic identification was equally accurate for topic-related images and topic sentences, and less accurate for unrelated images. Paragraphs from the text condition were recalled more accurately than the related and unrelated image conditions. Further, recognition of unrelated images was a positive predictor of the number of logical errors committed during recall. Therefore, related images did not improve memory and comprehension as much as text, and paragraphs with unrelated images negatively affected understanding of the meaning of the paragraph, but not recall. These findings have implications for multimedia information sources such as textbooks or articles that use images to clarify the meaning of the material.     

How unexpected observations lead to new beliefs: A Peircean pathway

People acquire new beliefs in various ways. One of the most important of these is that new beliefs are acquired as a response to experiencing events that one did not expect. This involves a form of inference distinct from both deductive and inductive inference: abductive inference. The concept of abduction is due to the American pragmatist philosopher C. S. Peirce. Davies and Coltheart (in press) elucidated what Peirce meant by abduction, and identified two problems in his otherwise promising account requiring solution if that account were to become fully workable. Here we propose solutions to these problems and offer an explicit cognitive model of how people derive new beliefs from observations of unexpected events, based on Peirce’s work and Sokolov’s ideas about prediction error triggering new beliefs. We consider that this model casts light not only upon normal processes of belief formation but also upon the formation of delusional beliefs.