Bryan C. Runck, Adam Streed, Diane Wang, Patrick M. Ewing, Michael B. Kantar, Barath Raghava. State spaces for agriculture: a metasystematic design automation framework.. 2022. agriXiv.2022.00158
State spaces for agriculture: a metasystematic design automation framework.
DOI: 10.31220/agriRxiv.2022.00158
Statement: This article is a preprint and has not been peer-reviewed. It reports new research that has yet to be evaluated and so should not be used to guide clinical practice.
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Abstract: Abstract Agriculture is a designed system with the largest areal footprint of any human activity. In some cases, the designs within agriculture emerged over thousands of years, such as the use of rows for the spatial organization of crops. In others, designs were deliberately chosen and implemented over decades as occurred during the Green Revolution. Currently, much work in agricultural science is focused on evaluating designs that could improve agriculture's sustainability. However, approaches to agricultural system design are diverse and fragmented, relying on individual intuition and discipline-specific methods for how to meet stakeholders' often semi-incompatible goals. This presents a risk that agricultural science will overlook non-obvious designs with large societal benefits. Here, we introduce a state space framework, a common approach from computer science, for agriculture to address the problem of proposing and evaluating designs computationally. This approach overcomes current limitations of agricultural system design by enabling a general set of computational abstractions to explore, and then select from, a much larger agricultural design set, which can then be empirically tested.
Key words: agriculture; designs; approach; agricultural; system design; evaluatinSubmit time: 1 January 2022
Copyright: The copyright holder for this preprint is the author/funder, who has granted agriXiv a license to display the preprint in perpetuity. -
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