toolbox memoir Search Results


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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).
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MathWorks Inc brain emotional learning simulink r toolbox
Fig. 7. The BELBIC <t>Simulink</t> R ⃝toolbox structure.
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MathWorks Inc learning toolbox in matlab
Fig. 7. The BELBIC <t>Simulink</t> R ⃝toolbox structure.
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MathWorks Inc statistics andmachine learning toolboxtm
Fig. 7. The BELBIC <t>Simulink</t> R ⃝toolbox structure.
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Image Search Results


(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:

Fig. 7. The BELBIC Simulink R ⃝toolbox structure.

Journal: IFAC-PapersOnLine

Article Title: A new brain emotional learning Simulink ® toolbox for control systems design * *This work was funded by the ERDF – European Regional Development Fund through the COMPETE Programme and by Portuguese funds through the FCT – Fundação para a Ciência e a Tecnologia within the project POCI-01-0145-FEDER-006961.

doi: 10.1016/j.ifacol.2017.08.1912

Figure Lengend Snippet: Fig. 7. The BELBIC Simulink R ⃝toolbox structure.

Article Snippet: The idea to develop a brain emotional learning Simulink R© toolbox is not new and has already been attempted by Mehrabian and Lucas (2006).

Techniques:

Journal: iScience

Article Title: Modeling early treatment response in AML from cell-free tumor DNA

doi: 10.1016/j.isci.2023.108271

Figure Lengend Snippet:

Article Snippet: Therefore, we used our internally developed MATLAB toolbox MEMOIR ( https://github.com/ICB-DCM/MEMOIR ) and fitted all patients simultaneously with a mixed effects modeling approach (see for details).

Techniques: Digital PCR, Mutagenesis, Software