The Problem of Coordination and the Pursuit of Structural Constraints in Psychology.

Paul Meehl's famous critique detailed many of the problematic practices and conceptual confusions that stand in the way of meaningful theoretical progress in psychological science. By integrating many of Meehl's points, we argue that one of the reasons for the slow progress in psychology is the failure to acknowledge the . This problem arises whenever we attempt to measure quantities that are not directly observable but can be inferred from observable variables.

A test of two processes: The effect of training on deductive and inductive reasoning.

Dual-process theories posit that separate kinds of intuitive (Type 1) and reflective (Type 2) processes contribute to reasoning. Under this view, inductive judgments are more heavily influenced by Type 1 processing, and deductive judgments are more strongly influenced by Type 2 processing. Alternatively, single-process theories propose that both types of judgments are based on a common form of assessment.

The effect of feedback delay on perceptual category learning and item memory: Further limits of multiple systems.

Delayed feedback during categorization training has been hypothesized to differentially affect 2 systems that underlie learning for rule-based (RB) or information-integration (II) structures. We tested an alternative possibility: that II learning requires more precise item representations than RB learning, and so is harmed more by a delay interval filled with a confusable mask. Experiments 1 and 2 examined the effect of feedback delay on memory for RB and II exemplars, both without and with concurrent categorization training.

More is generally better: Higher working memory capacity does not impair perceptual category learning.

It is sometimes supposed that category learning involves competing explicit and procedural systems, with only the former reliant on working memory capacity (WMC). In 2 experiments participants were trained for 3 blocks on both filtering (often said to be learned explicitly) and condensation (often said to be learned procedurally) category structures. Both experiments (total N = 160) demonstrated that participants with higher WMC tended to be more accurate in condensation tasks, but not less accurate in filtering tasks.

A rational model of function learning.

Theories of how people learn relationships between continuous variables have tended to focus on two possibilities: one, that people are estimating explicit functions, or two that they are performing associative learning supported by similarity. We provide a rational analysis of function learning, drawing on work on regression in machine learning and statistics. Using the equivalence of Bayesian linear regression and Gaussian processes, which provide a probabilistic basis for similarity-based function learning, we show that learning explicit rules and using similarity can be seen as two views of one solution to this problem.

State-trace analysis can be an appropriate tool for assessing the number of cognitive systems: a reply to Ashby (2014).

Ashby (2014) has argued that state-trace analysis (STA) is not an appropriate tool for assessing the number of cognitive systems, because it fails in its primary goal of distinguishing single-parameter and multiple-parameter models. We show that this is based on a misunderstanding of the logic of STA, which depends solely on nearly universal assumptions about psychological measurement and clearly supersedes inferences based on functional dissociation and the analysis of interactions in analyses of variance. We demonstrate that STA can be used to draw inferences concerning the number of latent variables mediating the effects of a set of independent variables on a set of dependent variables.

Revealing human inductive biases for category learning by simulating cultural transmission.

We explored people's inductive biases in category learning--that is, the factors that make learning category structures easy or hard--using iterated learning. This method uses the responses of one participant to train the next, simulating cultural transmission and converging on category structures that people find easy to learn. We applied this method to four different stimulus sets, varying in the identifiability of their underlying dimensions.

The effects of cultural transmission are modulated by the amount of information transmitted.

Information changes as it is passed from person to person, with this process of cultural transmission allowing the minds of individuals to shape the information that they transmit. We present mathematical models of cultural transmission which predict that the amount of information passed from person to person should affect the rate at which that information changes. We tested this prediction using a function-learning task, in which people learn a functional relationship between two variables by observing the values of those variables.

Learning and extrapolating a periodic function.

How people learn continuous functional relationships remains a poorly understood capacity. In this article, I argue that the mere presence of nonmonotonic extrapolation of periodic functions neither threatens existing theories of function learning nor distinguishes between them. However, I show that merely learning periodic functions is extremely difficult.

Working memory does not dissociate between different perceptual categorization tasks.

Working memory is crucial for many higher level cognitive functions, ranging from mental arithmetic to reasoning and problem solving. Likewise, the ability to learn and categorize novel concepts forms an indispensable part of human cognition. However, very little is known about the relationship between working memory and categorization.

The effect of feedback delay and feedback type on perceptual category learning: the limits of multiple systems.

Evidence that learning rule-based (RB) and information-integration (II) category structures can be dissociated across different experimental variables has been used to support the view that such learning is supported by multiple learning systems. Across 4 experiments, we examined the effects of 2 variables, the delay between response and feedback and the informativeness of feedback, which had previously been shown to dissociate learning of the 2 types of category structure. Our aim was twofold: first, to determine whether these dissociations meet the more stringent inferential criteria of state-trace analysis and, second, to determine the conditions under which they can be observed.

The Wisdom of Individuals: Exploring People's Knowledge About Everyday Events Using Iterated Learning.

Determining the knowledge that guides human judgments is fundamental to understanding how people reason, make decisions, and form predictions. We use an experimental procedure called ''iterated learning,'' in which the responses that people give on one trial are used to generate the data they see on the next, to pinpoint the knowledge that informs people's predictions about everyday events (e.g.

Review. Theoretical and empirical evidence for the impact of inductive biases on cultural evolution.

The question of how much the outcomes of cultural evolution are shaped by the cognitive capacities of human learners has been explored in several disciplines, including psychology, anthropology and linguistics. We address this question through a detailed investigation of transmission chains, in which each person passes information to another along a chain. We review mathematical and empirical evidence that shows that under general conditions, and across experimental paradigms, the information passed along transmission chains will be affected by the inductive biases of the people involved-the constraints on learning and memory, which influence conclusions from limited data.

Introduction. Cultural transmission and the evolution of human behaviour.

The articles in this theme issue seek to understand the evolutionary bases of social learning and the consequences of cultural transmission for the evolution of human behaviour. In this introductory article, we provide a summary of these articles (seven articles on the experimental exploration of cultural transmission and three articles on the role of gene-culture coevolution in shaping human behaviour) and a personal view of some promising lines of development suggested by the work summarized here.

Using category structures to test iterated learning as a method for identifying inductive biases.

Many of the problems studied in cognitive science are inductive problems, requiring people to evaluate hypotheses in the light of data. The key to solving these problems successfully is having the right inductive biases-assumptions about the world that make it possible to choose between hypotheses that are equally consistent with the observed data. This article explores a novel experimental method for identifying the biases that guide human inductive inferences.

Language evolution by iterated learning with bayesian agents.

Languages are transmitted from person to person and generation to generation via a process of iterated learning: people learn a language from other people who once learned that language themselves. We analyze the consequences of iterated learning for learning algorithms based on the principles of Bayesian inference, assuming that learners compute a posterior distribution over languages by combining a prior (representing their inductive biases) with the evidence provided by linguistic data. We show that when learners sample languages from this posterior distribution, iterated learning converges to a distribution over languages that is determined entirely by the prior.

Error-driven knowledge restructuring in categorization.

Knowledge restructuring occurs when people shift to a new strategy or representation during learning. Although knowledge restructuring can frequently be experimentally encouraged, there are instances in which people resist restructuring and continue to use an expedient but imperfect initial strategy. The authors report 3 category learning experiments that reconciled those conflicting outcomes by postulating that, for restructuring to occur, learners must be dissatisfied with their knowledge and a usable alternative must be available.

Population of linear experts: knowledge partitioning and function learning.

Knowledge partitioning is a theoretical construct holding that knowledge is not always integrated and homogeneous but may be separated into independent parcels containing mutually contradictory information. Knowledge partitioning has been observed in research on expertise, categorization, and function learning. This article presents a theory of function learning (the population of linear experts model--POLE) that assumes people partition their knowledge whenever they are presented with a complex task.

A multidimensional scaling approach to mental multiplication.

Adults consistently make errors in solving simple multiplication problems. These errors have been explained with reference to the interference between similar problems. In this paper, we apply multidimensional scaling (MDS) to the domain of multiplication problems, to uncover their underlying similarity structure.