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2000
Volume 11, Issue 5
  • ISSN: 1574-8936
  • E-ISSN: 2212-392X

Abstract

Background: One of the means to increase in-field crop yields is the use of software tools to predict future yield values using past in-field trials and plant genetics. The traditional, statistics-based approaches lack environmental data integration and are very sensitive to missing and/or noisy data. Objective: In this paper, we show that a cooperative, adaptive Multi-Agent System can overcome the drawbacks of such algorithms. Method: The system resolves the problem in an iterative way by a cooperation between the constraints, modelled as agents. Results: Results show that the Agent-Based Model gives results comparable to other approaches, without having to preprocess or reconcile data. Conclusion: This collective and self-adaptive search of a solution functions like a heuristic to efficiently explore the solution space and is therefore able to consider both genetic and environmental data.

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/content/journals/cbio/10.2174/1574893611666160617094329
2016-11-01
2025-05-22
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/content/journals/cbio/10.2174/1574893611666160617094329
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  • Article Type:
    Research Article
Keyword(s): Adaptation; environmental data; genomics; multi-agent systems; phenotypic prediction
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