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Humans learn and generate languages, music, games, and seemingly limitless varieties of other structures across domains. Unlike many AI systems, we often do so from little data. How do we learn such large varieties of richly structured representations so efficiently? One possibility is that people ``learn by programming,'' synthesizing data-generating algorithms to explain what we observe. We examine the nature and origins of this learning mechanism in adults, children, and nonhuman primates (macaque monkeys), using a highly unconstrained sequence prediction task. Although adults and children quickly learn many richly structured sequences, monkeys learn only the simplest sequences (e.g. lines). We test multiple learning models, finding that adults are best explained by a ``Language of Thought''-like program-learning model and monkeys by a simpler extrapolation strategy. Children exhibit varied learning strategies but are best fit in aggregate by an intermediately expressive model. Paper available at https://sites.google.com/view/patternlearning.

Human ecological success stems from our ability to absorb and build upon cultural knowledge, a process we aim to model computationally by integrating individual and cultural learning from language — one of the main vehicles of cultural transmission (e.g. instructions, explanations, stories). In simple video games, our model infers game rules from both interaction data (individual learning) and partial causal models extracted from game descriptions (cultural learning). Given exhaustive descriptions (either hand-written or generated by a model given access to oracle data), models leveraging the two learning sources induce more accurate game rules from limited data than both the individual- and cultural-only controls. Interestingly, descriptions from human game players do not consistently yield better rule induction. We hypothesize that players may preferentially communicate information that will be essential to the others' future decision-making and we aim to investigate cultural transmission by integrating individual and cultural learning with both causal understanding and decision-making.

Confidence is an important concept in cognitive science, as it integrates seamlessly with our beliefs, goals, and decisions. Humans naturally represent and express degrees of confidence in beliefs and predictions that reflect their accuracy. However, the dynamics of how our underlying beliefs about the world relate to explicitly represented confidence over those beliefs is yet not well understood. In this work, we make progress on this question in the domain of \textit{concept learning}. Specifically, we analyze how confidence and beliefs jointly evolve in the absence of explicit feedback. We evaluate some leading computational accounts of confidence in the present literature, and we find that these accounts do not accurately predict confidence in the context of our task. We advocate for caution in making claims about the generalizability of such accounts across tasks or domains and propose some new model-based measurements for predicting humans' confidence judgments. Of these measurements, we find that ones taking individual-level response patterns into account perform the best. We close by suggesting promising future directions for the study of confidence in concept learning.

Recent work in judgment and decision making has focused on which actions people consider when solving open-ended problems and found that the actions that come to mind tend to have particular features, such as having a high historical value. Here, we pursue the idea that the process of generating actions for decision-making tasks may actually reflect more general mechanisms for generating kinds of things. We provide evidence that what comes to mind may simply be a reflection of participants sampling from the most relevant part of the representational space they use to encode the type of thing they are generating. In this paper, we (1) introduce an approach for empirically describing a category in terms of the features that people use to represent category members, and for locating category members within that feature space, (2) show that certain locations in a category's feature space predict an item's likelihood of coming to mind, (3) introduce an approach for understanding the relevance of various features to people's representations of category members, and (4) show that features which are most involved in people's representations of category members are also predictors of what comes to mind within a category. We close by proposing that features that are most relevant to our representations of category members and predict coming to mind are those for which it has been historically useful to have information about during past experiences with the category in question.

Objective: The PARENTS 1 study (Parents' Active Role and ENgagement in The review of their Stillbirth/perinatal death) found that parents would endorse the opportunity to give feedback into the perinatal mortality review (PNMR) process. In subsequent focus groups, healthcare professionals were positive about parental engagement, although they considered that there may be significant challenges. The objective of this study was to develop core principles and recommendations for parental engagement in PNMR in the UK.Methods: A two-round Delphi technique was followed to reach consensus on core principles for parental engagement in the PNMR process; Round 1 included a national consensus workshop and Round 2 an online questionnaire. The consensus meeting was attended by a national panel of stakeholders (clinical and academic experts, parent advocates, managers and commissioners) in stillbirth and neonatal and bereavement care. To develop recommendations for parental engagement, participants discussed four key areas comprising: communication with parents, including receiving feedback; the format of the PNMR meeting; the parental engagement pathway; and challenging aspects of engaging with parents in reviews. Content analysis was conducted to generate recommendations from the meeting for a subsequent anonymous web-based survey. Attendees of the consensus workshop and members of the PARENTS 2 Project Advisory Board were asked to rank recommendations using a 9-point Likert scale from 1 (not important) to 9 (critically important). It had been agreed a priori, in compliance with established Grading of Recommendations, Assessment, Development and Evaluation (GRADE) criteria, that 'consensus' would be achieved if over 70% of participants scored the principle as 'critical' (score of 7-9) and fewer than 15% scored the principle as 'not important' (score of 1-3). Principles for which consensus was achieved were included in the core recommendations.Results: Of the 29 invited stakeholders, 22 participated in the consensus meeting and 25 (86% response rate) in the subsequent online questionnaire in June 2017. Consensus was agreed on 12 core principles. Of the 25 participants, 96% agreed that a face-to-face explanation of the PNMR process was of critical importance, 72% considered that parents should be offered the opportunity to nominate a suitable advocate, 92% believed that responses to parents' comments should be formally documented, 96% indicated that it was vital for action plans to be translated into lessons learnt and that this process should be monitored, and 100% of stakeholders voted that a plain-English summary should be produced for the parents following the meeting. There was good agreement on a further seven principles.Conclusions: Key national stakeholders were unanimously supportive of parental engagement in the PNMR process and agreed on core principles to make this process feasible, meaningful and robust. A 6-month pilot of parental engagement in the PNMR process (PARENTS 2 study) in two UK units took place after the consensus on core principles. In collaboration with the National Perinatal Epidemiology Unit, the findings will inform the national standardized PNMR tool. © 2018 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]