<p>Four tasks of 50 trials each are sequentially shown to the structure learning model. Priors were and . Marginal beliefs on reward probabilities (brightness indicates relative probability mass), probability of coupling and expected reward are shown as functions of time. <b>A</b>) Simulation on Independent Environment <b>B</b>) Simulation on Coupled Environment.</p
<p><b>A</b> and <b>B</b>) Performance of learning model and coupled model for decisions not predicte...
<p>Temporal evolution of p(t) for different simulation models in two types of interaction networks. ...
The development of a conceptual framework to build a model of multi-faceted choices underlying activ...
A. Example encoding stage representations of novel object images. Each subtask consists of images of...
a) The task (2-armed bandit) is represented like a binary choice task (blue or red squares), where t...
In all graphs, the collective strength G of the Go weights is depicted in green, while the negative ...
Any successful attempt at explaining and replicating the com-plexity and generality of human and ani...
This paper undertakes a simulation study of a player’s learning about the struc-ture of a game situa...
This paper undertakes a simulation study of a player’s learning about the structureof a game situati...
(A) Mean values of Cursor path area showing the progression of learning simulating results from the ...
This paper undertakes a simulation study of a player’s learning about the struc-ture of a game situa...
Recent work has shown that humans can learn or detect complex dependencies among variables. Even lea...
In the paper the simulation study is performed to inspect reliability of structure learning algorith...
<p>A: Schematic representation of the second task domain. Eight contexts (blue circles) were simulat...
Understanding how an animal’s ability to learn relates to neural activity or is altered by lesions, ...
<p><b>A</b> and <b>B</b>) Performance of learning model and coupled model for decisions not predicte...
<p>Temporal evolution of p(t) for different simulation models in two types of interaction networks. ...
The development of a conceptual framework to build a model of multi-faceted choices underlying activ...
A. Example encoding stage representations of novel object images. Each subtask consists of images of...
a) The task (2-armed bandit) is represented like a binary choice task (blue or red squares), where t...
In all graphs, the collective strength G of the Go weights is depicted in green, while the negative ...
Any successful attempt at explaining and replicating the com-plexity and generality of human and ani...
This paper undertakes a simulation study of a player’s learning about the struc-ture of a game situa...
This paper undertakes a simulation study of a player’s learning about the structureof a game situati...
(A) Mean values of Cursor path area showing the progression of learning simulating results from the ...
This paper undertakes a simulation study of a player’s learning about the struc-ture of a game situa...
Recent work has shown that humans can learn or detect complex dependencies among variables. Even lea...
In the paper the simulation study is performed to inspect reliability of structure learning algorith...
<p>A: Schematic representation of the second task domain. Eight contexts (blue circles) were simulat...
Understanding how an animal’s ability to learn relates to neural activity or is altered by lesions, ...
<p><b>A</b> and <b>B</b>) Performance of learning model and coupled model for decisions not predicte...
<p>Temporal evolution of p(t) for different simulation models in two types of interaction networks. ...
The development of a conceptual framework to build a model of multi-faceted choices underlying activ...