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Some work and some play: microscopic and macroscopic approaches to labor and leisure.

Niyogi RK, Shizgal P, Dayan P - PLoS Comput. Biol. (2014)

Bottom Line: However, averaging over the more microscopic processes that govern choices is known to pose tricky theoretical problems, and also eschews any possibility of direct contact with the neural computations involved.We develop a microscopic framework, formalized as a semi-Markov decision process with possibly stochastic choices, in which subjects approximately maximise their expected returns by making momentary commitments to one or other activity.We show macroscopic utilities that arise from microscopic ones, and demonstrate how facets such as imperfect substitutability can arise in a more straightforward microscopic manner.

View Article: PubMed Central - PubMed

Affiliation: Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.

ABSTRACT
Given the option, humans and other animals elect to distribute their time between work and leisure, rather than choosing all of one and none of the other. Traditional accounts of partial allocation have characterised behavior on a macroscopic timescale, reporting and studying the mean times spent in work or leisure. However, averaging over the more microscopic processes that govern choices is known to pose tricky theoretical problems, and also eschews any possibility of direct contact with the neural computations involved. We develop a microscopic framework, formalized as a semi-Markov decision process with possibly stochastic choices, in which subjects approximately maximise their expected returns by making momentary commitments to one or other activity. We show macroscopic utilities that arise from microscopic ones, and demonstrate how facets such as imperfect substitutability can arise in a more straightforward microscopic manner.

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Mountain model.Left panel: 3-dimensional relationship; right panel: contours of equal time allocation, as a function of reward intensity and price predicted by the mountain model using the generalised matching law. Red lines in right panel show : the price at which  for a maximal reward intensity (red dot in left panel). . The TA contours smoothly increase with reward intensity and smoothly decrease with price.
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pcbi-1003894-g005: Mountain model.Left panel: 3-dimensional relationship; right panel: contours of equal time allocation, as a function of reward intensity and price predicted by the mountain model using the generalised matching law. Red lines in right panel show : the price at which for a maximal reward intensity (red dot in left panel). . The TA contours smoothly increase with reward intensity and smoothly decrease with price.

Mentions: Here, is defined as the price at which, for a maximum subjective reward intensity , the subject allocates half the time to work, and half to leisure (see red lines in Figs.5 and S2A).


Some work and some play: microscopic and macroscopic approaches to labor and leisure.

Niyogi RK, Shizgal P, Dayan P - PLoS Comput. Biol. (2014)

Mountain model.Left panel: 3-dimensional relationship; right panel: contours of equal time allocation, as a function of reward intensity and price predicted by the mountain model using the generalised matching law. Red lines in right panel show : the price at which  for a maximal reward intensity (red dot in left panel). . The TA contours smoothly increase with reward intensity and smoothly decrease with price.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4256012&req=5

pcbi-1003894-g005: Mountain model.Left panel: 3-dimensional relationship; right panel: contours of equal time allocation, as a function of reward intensity and price predicted by the mountain model using the generalised matching law. Red lines in right panel show : the price at which for a maximal reward intensity (red dot in left panel). . The TA contours smoothly increase with reward intensity and smoothly decrease with price.
Mentions: Here, is defined as the price at which, for a maximum subjective reward intensity , the subject allocates half the time to work, and half to leisure (see red lines in Figs.5 and S2A).

Bottom Line: However, averaging over the more microscopic processes that govern choices is known to pose tricky theoretical problems, and also eschews any possibility of direct contact with the neural computations involved.We develop a microscopic framework, formalized as a semi-Markov decision process with possibly stochastic choices, in which subjects approximately maximise their expected returns by making momentary commitments to one or other activity.We show macroscopic utilities that arise from microscopic ones, and demonstrate how facets such as imperfect substitutability can arise in a more straightforward microscopic manner.

View Article: PubMed Central - PubMed

Affiliation: Gatsby Computational Neuroscience Unit, University College London, London, United Kingdom.

ABSTRACT
Given the option, humans and other animals elect to distribute their time between work and leisure, rather than choosing all of one and none of the other. Traditional accounts of partial allocation have characterised behavior on a macroscopic timescale, reporting and studying the mean times spent in work or leisure. However, averaging over the more microscopic processes that govern choices is known to pose tricky theoretical problems, and also eschews any possibility of direct contact with the neural computations involved. We develop a microscopic framework, formalized as a semi-Markov decision process with possibly stochastic choices, in which subjects approximately maximise their expected returns by making momentary commitments to one or other activity. We show macroscopic utilities that arise from microscopic ones, and demonstrate how facets such as imperfect substitutability can arise in a more straightforward microscopic manner.

Show MeSH