Computational Brain & Behavior

Công bố khoa học tiêu biểu

* Dữ liệu chỉ mang tính chất tham khảo

Sắp xếp:  
Alleviating the Cold Start Problem in Adaptive Learning using Data-Driven Difficulty Estimates
Computational Brain & Behavior - Tập 4 - Trang 231-249 - 2021
Maarten van der Velde, Florian Sense, Jelmer Borst, Hedderik van Rijn
An adaptive learning system offers a digital learning environment that adjusts itself to the individual learner and learning material. By refining its internal model of the learner and material over time, such a system continually improves its ability to present appropriate exercises that maximise learning gains. In many cases, there is an initial mismatch between the internal model and the learne...... hiện toàn bộ
Transfer of Learned Opponent Models in Zero Sum Games
Computational Brain & Behavior - Tập 5 - Trang 326-342 - 2022
Ismail Guennouni, Maarten Speekenbrink
Human learning transfer abilities take advantage of important cognitive building blocks such as an abstract representation of concepts underlying tasks and causal models of the environment. One way to build abstract representations of the environment when the task involves interactions with others is to build a model of the opponent that may inform what actions they are likely to take next. In thi...... hiện toàn bộ
The Experiment is just as Important as the Likelihood in Understanding the Prior: a Cautionary Note on Robust Cognitive Modeling
Computational Brain & Behavior - Tập 2 - Trang 210-217 - 2019
Lauren Kennedy, Daniel Simpson, Andrew Gelman
Cognitive modeling shares many features with statistical modeling, making it seem trivial to borrow from the practices of robust Bayesian statistics to protect the practice of robust cognitive modeling. We take one aspect of statistical workflow—prior predictive checks—and explore how they might be applied to a cognitive modeling task. We find that it is not only the likelihood that is needed to i...... hiện toàn bộ
A Sequential Sampling Approach to the Integration of Habits and Goals
Computational Brain & Behavior -
Chao Zhang, Arlette van Wissen, Ron Dotsch, Daniël Lakens, Wijnand A. IJsselsteijn
AbstractHabits often conflict with goal-directed behaviors and this phenomenon continues to attract interests from neuroscientists, experimental psychologists, and applied health psychologists. Recent computational models explain habit-goal conflicts as the competitions between two learning systems, arbitrated by a central unit. Based on recent research that combin...... hiện toàn bộ
A Comparison of Approximations for Base-Level Activation in ACT-R
Computational Brain & Behavior - Tập 1 - Trang 228-236 - 2018
Christopher R. Fisher, Joseph Houpt, Glenn Gunzelmann
Cognitive models provide a principled alternative for hypothesis testing and measuring individual differences. However, many cognitive models are computationally intensive to simulate, making their use difficult. Using approximations can make the application of cognitive models more tractable. We compare the standard and hybrid approximations of the base-level activation equation for the ACT-R cog...... hiện toàn bộ
Over-precise Predictions Cannot Identify Good Choice Models
Computational Brain & Behavior - - 2022
Nisheeth Srivastava, Nisheeth Srivastava
Approximating the Manifold Structure of Attributed Incentive Salience from Large-scale Behavioural Data
Computational Brain & Behavior - Tập 6 - Trang 280-315 - 2022
Valerio Bonometti, Mathieu J. Ruiz, Anders Drachen, Alex Wade
Incentive salience attribution can be understood as a psychobiological mechanism ascribing relevance to potentially rewarding objects and actions. Despite being an important component of the motivational process guiding our everyday behaviour its study in naturalistic contexts is not straightforward. Here we propose a methodology based on artificial neural networks (ANNs) for approximating latent ...... hiện toàn bộ
Variable-Drift Diffusion Models of Pedestrian Road-Crossing Decisions
Computational Brain & Behavior - Tập 5 - Trang 60-80 - 2021
Jami Pekkanen, Oscar Terence Giles, Yee Mun Lee, Ruth Madigan, Tatsuru Daimon, Natasha Merat, Gustav Markkula
Human behavior and interaction in road traffic is highly complex, with many open scientific questions of high applied importance, not least in relation to recent development efforts toward automated vehicles. In parallel, recent decades have seen major advances in cognitive neuroscience models of human decision-making, but these models have mainly been applied to simplified laboratory tasks. Here,...... hiện toàn bộ
A Multinomial Processing Tree Model of the 2-back Working Memory Task
Computational Brain & Behavior - Tập 5 - Trang 261-278 - 2022
Michael D. Lee, Percy K. Mistry, Vinod Menon
The n-back task is a widely used behavioral task for measuring working memory and the ability to inhibit interfering information. We develop a novel model of the commonly used 2-back task using the cognitive psychometric framework provided by Multinomial Processing Trees. Our model involves three parameters: a memory parameter, corresponding to how well an individual encodes and updates sequence i...... hiện toàn bộ
Hierarchical Hidden Markov Models for Response Time Data
Computational Brain & Behavior - Tập 4 Số 1 - Trang 70-86 - 2021
Deborah Kunkel, Zhifei Yan, Peter F. Craigmile, Mario Peruggia, Trisha Van Zandt
Tổng số: 139   
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 10