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Choice Behavior

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A Hierarchical Recurrent Neural Network for Symbolic Melody Generation.

IEEE transactions on cybernetics
In recent years, neural networks have been used to generate symbolic melodies. However, the long-term structure in the melody has posed great difficulty to design a good model. In this article, we present a hierarchical recurrent neural network (HRNN...

Quantifying influence of human choice on the automated detection of Drosophila behavior by a supervised machine learning algorithm.

PloS one
Automated quantification of behavior is increasingly prevalent in neuroscience research. Human judgments can influence machine-learning-based behavior classification at multiple steps in the process, for both supervised and unsupervised approaches. S...

A simple three layer excitatory-inhibitory neuronal network for temporal decision-making.

Behavioural brain research
Humans and animals do not only keep track of time intervals but they can also make decisions about durations. Temporal bisection is a psychophysical task that is widely used to assess the latter ability via categorization of durations as short or lon...

Categorization of digitized artworks by media with brain programming.

Applied optics
This work describes the use of brain programming applied to the categorization problem of art media. The art categorization problem-from the standpoint of materials and techniques used by artists-presents a challenging task and is considered an open ...

Experimentally revealed stochastic preferences for multicomponent choice options.

Journal of experimental psychology. Animal learning and cognition
Realistic, everyday rewards contain multiple components. An apple has taste and size. However, we choose in single dimensions, simply preferring some apples to others. How can such single-dimensional preference relationships refer to multicomponent c...

A dataset of human and robot approach behaviors into small free-standing conversational groups.

PloS one
The analysis and simulation of the interactions that occur in group situations is important when humans and artificial agents, physical or virtual, must coordinate when inhabiting similar spaces or even collaborate, as in the case of human-robot team...

Aesthetic preference for art can be predicted from a mixture of low- and high-level visual features.

Nature human behaviour
It is an open question whether preferences for visual art can be lawfully predicted from the basic constituent elements of a visual image. Here, we developed and tested a computational framework to investigate how aesthetic values are formed. We show...

Using large-scale experiments and machine learning to discover theories of human decision-making.

Science (New York, N.Y.)
Predicting and understanding how people make decisions has been a long-standing goal in many fields, with quantitative models of human decision-making informing research in both the social sciences and engineering. We show how progress toward this go...

Neural and computational mechanisms of momentary fatigue and persistence in effort-based choice.

Nature communications
From a gym workout, to deciding whether to persevere at work, many activities require us to persist in deciding that rewards are 'worth the effort' even as we become fatigued. However, studies examining effort-based decisions typically assume that th...