A step-by-step tutorial on active inference and its application to empirical data [0.03%]
基于主动推理的实证数据分析步骤教程
Ryan Smith,Karl J Friston,Christopher J Whyte
Ryan Smith
The active inference framework, and in particular its recent formulation as a partially observable Markov decision process (POMDP), has gained increasing popularity in recent years as a useful approach for modeling neurocognitive processes....
A hierarchical Bayesian state trace analysis for assessing monotonicity while factoring out subject, item, and trial level dependencies [0.03%]
一种分层贝叶斯状态痕迹分析方法：在考虑主体、项目和试验级别依赖性的同时评估单调性
Patrick Sadil,Rosemary A Cowell,David E Huber
Patrick Sadil
State trace analyses assess the latent dimensionality of a cognitive process by asking whether the means of two dependent variables conform to a monotonic function across a set of conditions. Using an assumption of independence between the ...
Lancelot Da Costa,Thomas Parr,Noor Sajid et al.
Lancelot Da Costa et al.
Active inference is a normative principle underwriting perception, action, planning, decision-making and learning in biological or artificial agents. From its inception, its associated process theory has grown to incorporate complex generat...
Farzin Shamloo,Sébastien Hélie
Farzin Shamloo
Humans and other animals are constantly learning new categories and making categorization decisions in their everyday life. However, different individuals may focus on different information when learning categories, which can impact the cat...
A Note on Decomposition of Sources of Variability in Perceptual Decision-making [0.03%]
关于感知决策中变异来源的分解问题
Inhan Kang,Roger Ratcliff,Chelsea Voskuilen
Inhan Kang
Information processing underlying human perceptual decision-making is inherently noisy and identifying sources of this noise is important to understand processing. Ratcliff, Voskuilen, and McKoon (2018) examined results from five experiment...
Simon Segert,Clintin P Davis-Stober
Simon Segert
We present a general method for setting prior distributions in Bayesian models where parameters of interest are re-parameterized via a functional relationship. We generalize the results of Heck and Wagenmakers (2016) by considering the case...
Fictional narrative as a variational Bayesian method for estimating social dispositions in large groups [0.03%]
虚构叙事在大型群体中估计社会倾向的变分贝叶斯方法
James Carney,Cole Robertson,Tamás Dávid-Barrett
James Carney
Modelling intentions in large groups is cognitively costly. Not alone must first order beliefs be tracked ('what does A think about X?'), but also beliefs about beliefs ('what does A think about B's belief concerning X?'). Thus linear incre...
Brandon M Turner,Birte U Forstmann,Bradley C Love et al.
Brandon M Turner et al.
Our understanding of cognition has been advanced by two traditionally nonoverlapping and non-interacting groups. Mathematical psychologists rely on behavioral data to evaluate formal models of cognition, whereas cognitive neuroscientists re...
Khanh P Nguyen,Krešimir Josić,Zachary P Kilpatrick
Khanh P Nguyen
To make decisions organisms often accumulate information across multiple timescales. However, most experimental and modeling studies of decision-making focus on sequences of independent trials. On the other hand, natural environments are ch...
Chandramouli Chandrasekaran,Steven P Blurton,Matthias Gondan
Chandramouli Chandrasekaran
In the redundant signals task, two target stimuli are associated with the same response. If both targets are presented together, redundancy gains are observed, as compared with single-target presentation. Different models explain these redu...