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Predicting Grass Growth for Sustainable Dairy Farming: A CBR System Using Bayesian Case-Exclusion and Post-Hoc, Personalized Explanation-by-Example (XAI)

  • Eoin M. KennyEmail author
  • Elodie Ruelle
  • Anne Geoghegan
  • Laurence Shalloo
  • Micheál O’Leary
  • Michael O’Donovan
  • Mark T. Keane
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11680)

Abstract

Smart agriculture has emerged as a rich application domain for AI-driven decision support systems (DSS) that support sustainable and responsible agriculture, by improving resource-utilization through better on-farm, management decisions. However, smart agriculture’s promise is often challenged by the high barriers to user adoption. This paper develops a case-based reasoning (CBR) system called PBI-CBR to predict grass growth for dairy farmers, that combines predictive accuracy and explanation capabilities designed to improve user adoption. The system provides post-hoc, personalized explanation-by-example for its predictions, by using explanatory cases from the same farm or county. A key novelty of PBI-CBR is its use of Bayesian methods for case exclusion in this regression domain. Experiments report the tradeoff that occurs between predictive accuracy and explanatory adequacy for different parametric variants of PBI-CBR, and how updating Bayesian priors each year reduces error.

Keywords

CBR Bayesian analysis Smart agriculture Case exclusion XAI 

Notes

Acknowledgements

This publication has emanated from research conducted with the financial support of (i) Science Foundation Ireland (SFI) to the Insight Centre for Data Analytics under Grant Number 12/RC/2289 and (ii) SFI and the Department of Agriculture, Food and Marine on behalf of the Government of Ireland to the VistaMilk SFI Research Centre under Grant Number 16/RC/3835.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Eoin M. Kenny
    • 1
    • 2
    • 4
    Email author
  • Elodie Ruelle
    • 3
    • 4
  • Anne Geoghegan
    • 3
    • 4
  • Laurence Shalloo
    • 3
    • 4
  • Micheál O’Leary
    • 3
    • 4
  • Michael O’Donovan
    • 3
    • 4
  • Mark T. Keane
    • 1
    • 2
    • 4
  1. 1.School of Computer ScienceUniversity College DublinDublinIreland
  2. 2.Insight Centre for Data AnalyticsUCDDublinIreland
  3. 3.Teagasc, Animal and Grassland ResearchFermoyIreland
  4. 4.VistaMilk SFI CentreFermoyIreland

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