about
Illusions of causality: how they bias our everyday thinking and how they could be reducedReasoning about causal relationships: Inferences on causal networksIllusion of control: the role of personal involvement.Causal learning about tolerance and sensitizationSpontaneous assimilation of continuous values and temporal information in causal induction.Implementation and assessment of an intervention to debias adolescents against causal illusions.Two heads are better than one, but how much? Evidence that people's use of causal integration rules does not always conform to normative standards.Effects of question formats on causal judgments and model evaluation.Neural computations mediating one-shot learning in the human brainAdapting to an Uncertain World: Cognitive Capacity and Causal Reasoning with Ambiguous Observations.Causal Networks or Causal Islands? The Representation of Mechanisms and the Transitivity of Causal Judgment.A cognitive neuroscience framework for understanding causal reasoning and the law.Dysphoric Mood States are Related to Sensitivity to Temporal Changes in ContingencyProbability matching in perceptrons: Effects of conditional dependence and linear nonseparability.Effect of grouping of evidence types on learning about interactions between observed and unobserved causesExpectations and interpretations during causal learningComparing associative, statistical, and inferential reasoning accounts of human contingency learningPathological gamblers are more vulnerable to the illusion of control in a standard associative learning taskA self-agency bias in preschoolers' causal inferences.BUCKLE: a model of unobserved cause learningSingle- and Dual-Process Models of Biased Contingency Detection.Previous knowledge can induce an illusion of causality through actively biasing behavior.Causal illusions in children when the outcome is frequent.Perceiving control over aversive and fearful events can alter how we experience those events: an investigation of time perception in spider-fearful individuals.Outcome probability modulates anticipatory behavior to signals that are equally reliable.How multiple causes combine: independence constraints on causal inference.Causal structure learning over time: observations and interventions.Causal imprinting in causal structure learning.A machine learning model with human cognitive biases capable of learning from small and biased datasets.
P2860
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P2860
description
1965 nî lūn-bûn
@nan
1965 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
1965 թվականի հունվարին հրատարակված գիտական հոդված
@hy
1965年の論文
@ja
1965年論文
@yue
1965年論文
@zh-hant
1965年論文
@zh-hk
1965年論文
@zh-mo
1965年論文
@zh-tw
1965年论文
@wuu
name
JUDGMENT OF CONTINGENCY BETWEEN RESPONSES AND OUTCOMES.
@ast
JUDGMENT OF CONTINGENCY BETWEEN RESPONSES AND OUTCOMES.
@en
JUDGMENT OF CONTINGENCY BETWEEN RESPONSES AND OUTCOMES.
@nl
type
label
JUDGMENT OF CONTINGENCY BETWEEN RESPONSES AND OUTCOMES.
@ast
JUDGMENT OF CONTINGENCY BETWEEN RESPONSES AND OUTCOMES.
@en
JUDGMENT OF CONTINGENCY BETWEEN RESPONSES AND OUTCOMES.
@nl
prefLabel
JUDGMENT OF CONTINGENCY BETWEEN RESPONSES AND OUTCOMES.
@ast
JUDGMENT OF CONTINGENCY BETWEEN RESPONSES AND OUTCOMES.
@en
JUDGMENT OF CONTINGENCY BETWEEN RESPONSES AND OUTCOMES.
@nl
P1476
JUDGMENT OF CONTINGENCY BETWEEN RESPONSES AND OUTCOMES.
@en
P2093
P304
SUPPL 1:1-17
P577
1965-01-01T00:00:00Z