Computational Brain & Behavior
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Hierarchical Reinforcement Learning Explains Task Interleaving Behavior
Computational Brain & Behavior - - 2020
How do people decide how long to continue in a task, when to switch, and to which other task? It is known that task interleaving adapts situationally, showing sensitivity to changes in expected rewards, costs, and task boundaries. However, the mechanisms that underpin the decision to stay in a task versus switch away are not thoroughly understood. Previous work has explained task interleaving by g...... hiện toàn bộ
Similarity-Based Interference in Sentence Comprehension in Aphasia: a Computational Evaluation of Two Models of Cue-Based Retrieval
Computational Brain & Behavior - Tập 6 Số 3 - Trang 473-502 - 2023
Sentence comprehension requires the listener to link incoming words with short-term memory representations in order to build linguistic dependencies. The cue-based retrieval theory of sentence processing predicts that the retrieval of these memory representations is affected by similarity-based interference. We present the first large-scale computational evaluation of interference effects in two m...... hiện toàn bộ
On the Measure-Theoretic Premises of Bayes Factor and Full Bayesian Significance Tests: a Critical Reevaluation
Computational Brain & Behavior - Tập 5 - Trang 572-582 - 2021
The Full Bayesian Significance Test (FBST) and the Bayesian evidence value recently have received increasing attention across a variety of sciences including psychology. Ly and Wagenmakers (2021) have provided a critical evaluation of the method and concluded that it suffers from four problems which are mostly attributed to the asymptotic relationship of the Bayesian evidence value to the frequent...... hiện toàn bộ
The Relationship Between Environmental Statistics and Predictive Gaze Behaviour During a Manual Interception Task: Eye Movements as Active Inference
Computational Brain & Behavior - - Trang 1-17 - 2023
Human observers are known to frequently act like Bayes-optimal decision-makers. Growing evidence indicates that the deployment of the visual system may similarly be driven by probabilistic mental models of the environment. We tested whether eye movements during a dynamic interception task were indeed optimised according to Bayesian inference principles. Forty-one participants intercepted oncoming ...... hiện toàn bộ
Detecting Strategies in Developmental Psychology
Computational Brain & Behavior - Tập 2 - Trang 128-140 - 2019
Differential strategy use is a topic of intense investigation in developmental psychology. Questions under study are as follows: How do strategies change with age, how can individual differences in strategy use be explained, and which interventions promote shifts from suboptimal to optimal strategies? In order to detect such differential strategy use, developmental psychology currently relies on t...... hiện toàn bộ
Reconstructing the Einstellung Effect
Computational Brain & Behavior - Tập 6 - Trang 526-542 - 2022
The Einstellung effect was first described by Abraham Luchins in his doctoral thesis published in 1942. The effect occurs when a repeated solution to old problems is applied to a new problem even though a more appropriate response is available. In Luchins’ so-called water jar task, participants had to measure a specific amount of water using three jars of different capacities. Luchins found that s...... hiện toàn bộ
Nâng cao Quyết định của Con người với các Trợ giúp Quyết định Tạo ra Bằng AI Dịch bởi AI
Computational Brain & Behavior - Tập 5 - Trang 467-490 - 2022
Quyết định của con người thường gặp phải nhiều sai lầm hệ thống. Nhiều trong số các sai lầm này có thể tránh được bằng cách cung cấp các trợ giúp quyết định hướng dẫn người ra quyết định chú ý đến thông tin quan trọng và tích hợp nó theo một chiến lược quyết định hợp lý. Thiết kế các trợ giúp quyết định như vậy trước đây là một quá trình thủ công tốn thời gian. Các tiến bộ trong khoa học nhận thức...... hiện toàn bộ
#quyết định con người #các lỗi hệ thống #trợ giúp quyết định #học máy #tự động hóa #hướng dẫn quy trình #lập kế hoạch #thế chấp
When Fixed and Random Effects Mismatch: Another Case of Inflation of Evidence in Non-Maximal ModelsAbstract Mixed-effects models that include both fixed and random effects are widely used in the cognitive sciences because they are particularly suited to the analysis of clustered data. However, testing hypotheses about fixed effects in the presence of random effects is far from straightforward and a set of best practices is still lacking. In the target article, va... ... hiện toàn bộ
Computational Brain & Behavior - Tập 6 Số 1 - Trang 84-101 - 2023
Actively Learning to Learn Causal Relationships
Computational Brain & Behavior - - Trang 1-26 - 2024
How do people actively learn to learn? That is, how and when do people choose actions that facilitate long-term learning and choosing future actions that are more informative? We explore these questions in the domain of active causal learning. We propose a hierarchical Bayesian model that goes beyond past models by predicting that people pursue information not only about the causal relationship at...... hiện toàn bộ
Externally Provided Rewards Increase Internal Preference, but Not as Much as Preferred Ones Without Extrinsic Rewards
Computational Brain & Behavior - - 2024
It is well known that preferences are formed through choices, known as choice-induced preference change (CIPC). However, whether value learned through externally provided rewards influences the preferences formed through CIPC remains unclear. To address this issue, we used tasks for decision-making guided by reward provided by the external environment (externally guided decision-making; EDM) and f...... hiện toàn bộ
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