Bayesian Case-Exclusion and Personalized Explanations for Sustainable Dairy Farming (Extended Abstract)

Eoin M. Kenny, Elodie Ruelle, Anne Geoghegan, Laurence Shalloo, Micheál O'Leary, Michael O'Donovan, Mohammed Temraz, Mark T. Keane
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
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 (CBR) 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
more » ... e accuracy and explanatory capability for different variants of PBI-CBR, and how updating Bayesian priors each year improves performance.
doi:10.24963/ijcai.2020/649 dblp:conf/ijcai/ChenSHLML20 fatcat:cjn73bwpqzdcheoctkkl62fokq