A Bayesian Model of the Rule Association Task and Effect of Priming
نویسنده
چکیده
This paper describes a normative model of the Rule Association task based on Bayesian inference and formulated in discrete time. We also show how it reduces to a standard Drift Diffusion Model in the continuum limit. This relationship then provides semi-analytic formulae for the mean reaction time and error rate. The model is applied to behavioral data from an experiment where we used priming to manipulate subjects ability to perform the task.
منابع مشابه
Semantic Priming Effect on Relative Clause Attachment Ambiguity Resolution in L2
This study examined whether processing ambiguous sentences containing relative clauses (RCs) following a complex determiner phrase (DP) by Persian-speaking learners of L2 English with different proficiency and working memory capacities (WMCs) is affected by semantic priming. The semantic relationship studied was one between the subject/verb of the main clause and one of the DPs in the complex D...
متن کاملMental Representation of Cognates/Noncognates in Persian-Speaking EFL Learners
The purpose of this study was to investigate the mental representation of cognate and noncognate translation pairs in languages with different scripts to test the prediction of dual lexicon model (Gollan, Forster, & Frost, 1997). Two groups of Persian-speaking English language learners were tested on cognate and noncognate translation pairs in Persian-English and English-Persian directions with...
متن کاملSelf-Associations Influence Task-Performance through Bayesian Inference
The way we think about ourselves impacts greatly on our behavior. This paper describes a behavioral study and a computational model that shed new light on this important area. Participants were primed "clever" and "stupid" using a scrambled sentence task, and we measured the effect on response time and error-rate on a rule-association task. First, we observed a confirmation bias effect in that ...
متن کاملDisTriB: Distributed Trust Management Model Based on Gossip Learning and Bayesian Networks in Collaborative Computing Systems
The interactions among peers in Peer-to-Peer systems as a distributed collaborative system are based on asynchronous and unreliable communications. Trust is an essential and facilitating component in these interactions specially in such uncertain environments. Various attacks are possible due to large-scale nature and openness of these systems that affects the trust. Peers has not enough inform...
متن کاملDisTriB: Distributed Trust Management Model Based on Gossip Learning and Bayesian Networks in Collaborative Computing Systems
The interactions among peers in Peer-to-Peer systems as a distributed collaborative system are based on asynchronous and unreliable communications. Trust is an essential and facilitating component in these interactions specially in such uncertain environments. Various attacks are possible due to large-scale nature and openness of these systems that affects the trust. Peers has not enough inform...
متن کامل