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

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

University College Dublin
Insight Centre for Data Analytics
Teagasc - Irish Agriculture and Food Development Authority
VistaMilk SFI Research Centre

Research output: Chapter in Book/Report/Conference proceedings › Conference proceeding › peer-review

Abstract

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, combining predictive accuracy and explanations to improve user adoption. PBI-CBR's novelty lies in the use of Bayesian methods for case-base maintenance in a regression domain. Experiments report the tradeoff between predictive accuracy and explanatory capability for variants of PBI-CBR, and how updating Bayesian priors each year improves performance.

Original language	English
Title of host publication	Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI 2020
Editors	Christian Bessiere
Publisher	International Joint Conferences on Artificial Intelligence
Pages	4740-4744
Number of pages	5
ISBN (Electronic)	9780999241165
Publication status	Published - 2020
Externally published	Yes
Event	29th International Joint Conference on Artificial Intelligence, IJCAI 2020 - Yokohama, Japan Duration: 1 Jan 2021 → …

Publication series

Name	IJCAI International Joint Conference on Artificial Intelligence
Volume	2021-January
ISSN (Print)	1045-0823

Conference

Conference	29th International Joint Conference on Artificial Intelligence, IJCAI 2020
Country/Territory	Japan
City	Yokohama
Period	1/01/21 → …

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 2 Zero Hunger

Cite this

Kenny, E. M., Ruelle, E., Geoghegan, A., Shalloo, L., O'Leary, M., O'Donovan, M., Temraz, M., & Keane, M. T. (2020). Bayesian case-exclusion and personalized explanations for sustainable dairy farming (extended abstract). In C. Bessiere (Ed.), Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI 2020 (pp. 4740-4744). (IJCAI International Joint Conference on Artificial Intelligence; Vol. 2021-January). International Joint Conferences on Artificial Intelligence.

Kenny, Eoin M. ; Ruelle, Elodie ; Geoghegan, Anne et al. / Bayesian case-exclusion and personalized explanations for sustainable dairy farming (extended abstract). Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI 2020. editor / Christian Bessiere. International Joint Conferences on Artificial Intelligence, 2020. pp. 4740-4744 (IJCAI International Joint Conference on Artificial Intelligence).

@inproceedings{3af8a479d78c474d8e384e1ca9c29124,

title = "Bayesian case-exclusion and personalized explanations for sustainable dairy farming (extended abstract)",

abstract = "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, combining predictive accuracy and explanations to improve user adoption. PBI-CBR's novelty lies in the use of Bayesian methods for case-base maintenance in a regression domain. Experiments report the tradeoff between predictive accuracy and explanatory capability for variants of PBI-CBR, and how updating Bayesian priors each year improves performance.",

author = "Kenny, \{Eoin M.\} and Elodie Ruelle and Anne Geoghegan and Laurence Shalloo and Miche{\'a}l O'Leary and Michael O'Donovan and Mohammed Temraz and Keane, \{Mark T.\}",

note = "Publisher Copyright: {\textcopyright} 2020 Inst. Sci. inf., Univ. Defence in Belgrade. All rights reserved.; 29th International Joint Conference on Artificial Intelligence, IJCAI 2020 ; Conference date: 01-01-2021",

year = "2020",

language = "English",

series = "IJCAI International Joint Conference on Artificial Intelligence",

publisher = "International Joint Conferences on Artificial Intelligence",

pages = "4740--4744",

editor = "Christian Bessiere",

booktitle = "Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI 2020",

address = "United States",

}

Kenny, EM, Ruelle, E, Geoghegan, A, Shalloo, L, O'Leary, M, O'Donovan, M, Temraz, M & Keane, MT 2020, Bayesian case-exclusion and personalized explanations for sustainable dairy farming (extended abstract). in C Bessiere (ed.), Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI 2020. IJCAI International Joint Conference on Artificial Intelligence, vol. 2021-January, International Joint Conferences on Artificial Intelligence, pp. 4740-4744, 29th International Joint Conference on Artificial Intelligence, IJCAI 2020, Yokohama, Japan, 1/01/21.

Bayesian case-exclusion and personalized explanations for sustainable dairy farming (extended abstract). / Kenny, Eoin M.; Ruelle, Elodie; Geoghegan, Anne et al.
Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI 2020. ed. / Christian Bessiere. International Joint Conferences on Artificial Intelligence, 2020. p. 4740-4744 (IJCAI International Joint Conference on Artificial Intelligence; Vol. 2021-January).

Research output: Chapter in Book/Report/Conference proceedings › Conference proceeding › peer-review

TY - GEN

T1 - Bayesian case-exclusion and personalized explanations for sustainable dairy farming (extended abstract)

AU - Kenny, Eoin M.

AU - Ruelle, Elodie

AU - Geoghegan, Anne

AU - Shalloo, Laurence

AU - O'Leary, Micheál

AU - O'Donovan, Michael

AU - Temraz, Mohammed

AU - Keane, Mark T.

PY - 2020

Y1 - 2020

N2 - 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, combining predictive accuracy and explanations to improve user adoption. PBI-CBR's novelty lies in the use of Bayesian methods for case-base maintenance in a regression domain. Experiments report the tradeoff between predictive accuracy and explanatory capability for variants of PBI-CBR, and how updating Bayesian priors each year improves performance.

AB - 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, combining predictive accuracy and explanations to improve user adoption. PBI-CBR's novelty lies in the use of Bayesian methods for case-base maintenance in a regression domain. Experiments report the tradeoff between predictive accuracy and explanatory capability for variants of PBI-CBR, and how updating Bayesian priors each year improves performance.

UR - https://www.scopus.com/pages/publications/85097344843

M3 - Conference proceeding

AN - SCOPUS:85097344843

T3 - IJCAI International Joint Conference on Artificial Intelligence

SP - 4740

EP - 4744

BT - Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI 2020

A2 - Bessiere, Christian

PB - International Joint Conferences on Artificial Intelligence

T2 - 29th International Joint Conference on Artificial Intelligence, IJCAI 2020

Y2 - 1 January 2021

ER -

Kenny EM, Ruelle E, Geoghegan A, Shalloo L, O'Leary M, O'Donovan M et al. Bayesian case-exclusion and personalized explanations for sustainable dairy farming (extended abstract). In Bessiere C, editor, Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI 2020. International Joint Conferences on Artificial Intelligence. 2020. p. 4740-4744. (IJCAI International Joint Conference on Artificial Intelligence).

Bayesian case-exclusion and personalized explanations for sustainable dairy farming (extended abstract)

Abstract

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Conference

UN SDGs

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