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Bayesian Case-Exclusion and Explainable AI (XAI) for Sustainable Farming
2021-01-15, Kenny, Eoin M., Ruelle, Elodie, Geoghegan, Anne, Temraz, Mohammed, Keane, Mark T., et al.
Smart agriculture (SmartAg) has emerged as a rich domain for AI-driven decision support systems (DSS); however, it is often challenged by user-adoption issues. This paper reports a case-based reasoning system, PBI-CBR, that predicts grass growth for dairy farmers, that combines predictive accuracy and explanations to improve user adoption. PBI-CBR’s key novelty is its use of Bayesian methods for case-base maintenance in a regression domain. Experiments report the tradeoff between predictive accuracy and explanatory capability for different variants of PBI-CBR, and how updating Bayesian priors each year improves performance.