Harman, Helen and Sklar, Elizabeth I. (2022) Challenges for Multi-Agent Based Agricultural Workforce Management. In: The 23rd International Workshop on Multi-Agent-Based Simulation (MABS)).
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MABS_2022_paper_8137.pdf - Whole Document Restricted to Repository staff only until 9 May 2023. 464kB |
Item Type: | Conference or Workshop contribution (Paper) |
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Item Status: | Live Archive |
Abstract
Multi-agent task allocation methods seek to distribute a set of tasks fairly amongst a set of agents. In real-world settings, such as soft fruit farms, human labourers undertake harvesting tasks, assigned by farm managers. The work here explores the application of artificial intelligence planning methodologies to optimise the existing workforce and applies multi-agent based simulation to evaluate the efficacy of the AI strategies. Key challenges threatening the acceptance of such an approach are highlighted and solutions are evaluated experimentally.
Keywords: | agriculture, multi-agent based simulation, task allocation |
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Subjects: | G Mathematical and Computer Sciences > G700 Artificial Intelligence |
Divisions: | College of Science > Lincoln Institute for Agri-Food Technology |
ID Code: | 49036 |
Deposited On: | 04 May 2022 07:51 |
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