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

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  • Spyridon Samothrakis

Abstract

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.

Suggested Citation

  • Spyridon Samothrakis, 2021. "Artificial Intelligence inspired methods for the allocation of common goods and services," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-16, September.
    • Handle: RePEc:plo:pone00:0257399
    DOI: 10.1371/journal.pone.0257399
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    1. Julian Schrittwieser & Ioannis Antonoglou & Thomas Hubert & Karen Simonyan & Laurent Sifre & Simon Schmitt & Arthur Guez & Edward Lockhart & Demis Hassabis & Thore Graepel & Timothy Lillicrap & David , 2020. "Mastering Atari, Go, chess and shogi by planning with a learned model," Nature, Nature, vol. 588(7839), pages 604-609, December.
    2. Ellman,Michael, 2014. "Socialist Planning," Cambridge Books, Cambridge University Press, number 9781107074736, Enero-Abr.
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