Artificial Intelligence inspired methods for the allocation of common goods and services.

The debate over the optimal way of allocating societal surplus (i.e. products and services) has been raging, in one form or another, practically forever; following the collapse of the Soviet Union in 1991, the market has taken the lead vs the public sector to do this. Working within the tradition of...

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Autor principal:	Spyridon Samothrakis
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f01e44463ca04f8fbbd796d74ce874da
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spelling	oai:doaj.org-article:f01e44463ca04f8fbbd796d74ce874da2021-12-02T20:06:08ZArtificial Intelligence inspired methods for the allocation of common goods and services.1932-620310.1371/journal.pone.0257399https://doaj.org/article/f01e44463ca04f8fbbd796d74ce874da2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0257399https://doaj.org/toc/1932-6203The debate over the optimal way of allocating societal surplus (i.e. products and services) has been raging, in one form or another, practically forever; following the collapse of the Soviet Union in 1991, the market has taken the lead vs the public sector to do this. Working within the tradition of Marx, Leontief, Beer and Cockshott, we propose what we deem an automated planning system that aims to operate on unit level (e.g., factories and citizens), rather than on aggregate demand and sectors. We explain why it is both a viable and desirable alternative to current market conditions and position our solution within current societal structures. Our experiments show that it would be trivial to plan for up to 50K industrial goods and 5K final goods in commodity hardware. Our approach bridges the gap between traditional planning methods and modern AI planning, opening up venues for further research.Spyridon SamothrakisPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 9, p e0257399 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Spyridon Samothrakis Artificial Intelligence inspired methods for the allocation of common goods and services.
description	The debate over the optimal way of allocating societal surplus (i.e. products and services) has been raging, in one form or another, practically forever; following the collapse of the Soviet Union in 1991, the market has taken the lead vs the public sector to do this. Working within the tradition of Marx, Leontief, Beer and Cockshott, we propose what we deem an automated planning system that aims to operate on unit level (e.g., factories and citizens), rather than on aggregate demand and sectors. We explain why it is both a viable and desirable alternative to current market conditions and position our solution within current societal structures. Our experiments show that it would be trivial to plan for up to 50K industrial goods and 5K final goods in commodity hardware. Our approach bridges the gap between traditional planning methods and modern AI planning, opening up venues for further research.
format	article
author	Spyridon Samothrakis
author_facet	Spyridon Samothrakis
author_sort	Spyridon Samothrakis
title	Artificial Intelligence inspired methods for the allocation of common goods and services.
title_short	Artificial Intelligence inspired methods for the allocation of common goods and services.
title_full	Artificial Intelligence inspired methods for the allocation of common goods and services.
title_fullStr	Artificial Intelligence inspired methods for the allocation of common goods and services.
title_full_unstemmed	Artificial Intelligence inspired methods for the allocation of common goods and services.
title_sort	artificial intelligence inspired methods for the allocation of common goods and services.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/f01e44463ca04f8fbbd796d74ce874da
work_keys_str_mv	AT spyridonsamothrakis artificialintelligenceinspiredmethodsfortheallocationofcommongoodsandservices
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Artificial Intelligence inspired methods for the allocation of common goods and services.

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