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Abbott Laboratories reinforcement learning (rl) model
Reinforcement Learning (Rl) Model, supplied by Abbott Laboratories, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/reinforcement+learning+(rl)+model/reinforcement+learning/pm38922495-37-9-39
Average 90 stars, based on 1 article reviews
reinforcement learning (rl) model - by Bioz Stars, 2026-09
90/100 stars

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Article Title: Internally Formed Preferences for Options only Influence Initial Decisions in Gambling Tasks, while the Gambling Outcomes do not Alter these Preferences.
Article Snippet: For estimating the value in EDM, we used the reinforcement learning (RL) model (Sutton & Barto, 1998; Watkins & Dayan, 1992), which has been widely used to explain the value-learning mechanism in EDM (Daw & Doya, 2006; Dayan & Abbott, 2005; Dayan & Balleine, 2002; Gläscher et al., 2010; Schönberg et al., 2007).



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Abbott Laboratories reinforcement learning (rl) model
Reinforcement Learning (Rl) Model, supplied by Abbott Laboratories, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/reinforcement+learning+(rl)+model/reinforcement+learning/pm38922495-37-9-39
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MathWorks Inc reinforcement learning rl models fit behavior
(A) <t>Reinforcement</t> schedule by trustee and block; (B) Trial design. Counterfactual feedback is presented to participants after “KEEP” decisions (top panel).
Reinforcement Learning Rl Models Fit Behavior, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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(A) Reinforcement schedule by trustee and block; (B) Trial design. Counterfactual feedback is presented to participants after “KEEP” decisions (top panel).

Journal: Cognitive, affective & behavioral neuroscience

Article Title: Neurocomputational mechanisms of adaptive learning in social exchanges

doi: 10.3758/s13415-019-00697-0

Figure Lengend Snippet: (A) Reinforcement schedule by trustee and block; (B) Trial design. Counterfactual feedback is presented to participants after “KEEP” decisions (top panel).

Article Snippet: We used the Variational Bayes Approach (VBA) toolbox implemented in MATLAB ( Daunizeau, Adam, & Rigoux, 2014 ) to test how four reinforcement learning (RL) models fit behavior (likelihood of sharing).

Techniques: Blocking Assay

(A) Observed probability of investing by reputation (trustee type) in Studies 1–3; (B) Predicted likelihood of investing by previous trustee decision and exchange number (previous trustee decision × exchange number), indicating the growing effect of reinforcement as the participant leams (adaptive learning).

Journal: Cognitive, affective & behavioral neuroscience

Article Title: Neurocomputational mechanisms of adaptive learning in social exchanges

doi: 10.3758/s13415-019-00697-0

Figure Lengend Snippet: (A) Observed probability of investing by reputation (trustee type) in Studies 1–3; (B) Predicted likelihood of investing by previous trustee decision and exchange number (previous trustee decision × exchange number), indicating the growing effect of reinforcement as the participant leams (adaptive learning).

Article Snippet: We used the Variational Bayes Approach (VBA) toolbox implemented in MATLAB ( Daunizeau, Adam, & Rigoux, 2014 ) to test how four reinforcement learning (RL) models fit behavior (likelihood of sharing).

Techniques: