Dependency provenance in agent based modeling

Peng Chen, Beth Plale, Tom Evans

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Researchers who use agent-based models (ABM) to model social patterns often focus on the model's aggregate phenomena. However, aggregation of individuals complicates the understanding of agent interactions and the uniqueness of individuals. We develop a method for tracing and capturing the provenance of individuals and their interactions in the NetLogo ABM, and from this create a "dependency provenance slice", which combines a data slice and a program slice to yield insights into the cause-effect relations among system behaviors. To cope with the large volume of fine-grained provenance traces, we propose use-inspired filters to reduce the amount of provenance, and a provenance slicing technique called "non-preprocessing provenance slicing" that directly queries over provenance traces without recovering all provenance entities and dependencies beforehand. We evaluate performance and utility using a well known ecological NetLogo model called "wolf-sheep- predation".

Original languageEnglish (US)
Title of host publicationProceedings - IEEE 9th International Conference on e-Science, e-Science 2013
PublisherIEEE Computer Society
Pages180-187
Number of pages8
ISBN (Print)9780768550831
DOIs
StatePublished - Jan 1 2013
Externally publishedYes
Event9th IEEE International Conference on e-Science, e-Science 2013 - Beijing, China
Duration: Oct 22 2013Oct 25 2013

Publication series

NameProceedings - IEEE 9th International Conference on e-Science, e-Science 2013

Conference

Conference9th IEEE International Conference on e-Science, e-Science 2013
CountryChina
CityBeijing
Period10/22/1310/25/13

Fingerprint

Agglomeration

ASJC Scopus subject areas

  • Information Systems

Cite this

Chen, P., Plale, B., & Evans, T. (2013). Dependency provenance in agent based modeling. In Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013 (pp. 180-187). [6683906] (Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013). IEEE Computer Society. https://doi.org/10.1109/eScience.2013.39

Dependency provenance in agent based modeling. / Chen, Peng; Plale, Beth; Evans, Tom.

Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013. IEEE Computer Society, 2013. p. 180-187 6683906 (Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chen, P, Plale, B & Evans, T 2013, Dependency provenance in agent based modeling. in Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013., 6683906, Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013, IEEE Computer Society, pp. 180-187, 9th IEEE International Conference on e-Science, e-Science 2013, Beijing, China, 10/22/13. https://doi.org/10.1109/eScience.2013.39
Chen P, Plale B, Evans T. Dependency provenance in agent based modeling. In Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013. IEEE Computer Society. 2013. p. 180-187. 6683906. (Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013). https://doi.org/10.1109/eScience.2013.39
Chen, Peng ; Plale, Beth ; Evans, Tom. / Dependency provenance in agent based modeling. Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013. IEEE Computer Society, 2013. pp. 180-187 (Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013).
@inproceedings{14c54811fc57417d872e3d6fc0ea06d1,
title = "Dependency provenance in agent based modeling",
abstract = "Researchers who use agent-based models (ABM) to model social patterns often focus on the model's aggregate phenomena. However, aggregation of individuals complicates the understanding of agent interactions and the uniqueness of individuals. We develop a method for tracing and capturing the provenance of individuals and their interactions in the NetLogo ABM, and from this create a {"}dependency provenance slice{"}, which combines a data slice and a program slice to yield insights into the cause-effect relations among system behaviors. To cope with the large volume of fine-grained provenance traces, we propose use-inspired filters to reduce the amount of provenance, and a provenance slicing technique called {"}non-preprocessing provenance slicing{"} that directly queries over provenance traces without recovering all provenance entities and dependencies beforehand. We evaluate performance and utility using a well known ecological NetLogo model called {"}wolf-sheep- predation{"}.",
author = "Peng Chen and Beth Plale and Tom Evans",
year = "2013",
month = "1",
day = "1",
doi = "10.1109/eScience.2013.39",
language = "English (US)",
isbn = "9780768550831",
series = "Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013",
publisher = "IEEE Computer Society",
pages = "180--187",
booktitle = "Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013",

}

TY - GEN

T1 - Dependency provenance in agent based modeling

AU - Chen, Peng

AU - Plale, Beth

AU - Evans, Tom

PY - 2013/1/1

Y1 - 2013/1/1

N2 - Researchers who use agent-based models (ABM) to model social patterns often focus on the model's aggregate phenomena. However, aggregation of individuals complicates the understanding of agent interactions and the uniqueness of individuals. We develop a method for tracing and capturing the provenance of individuals and their interactions in the NetLogo ABM, and from this create a "dependency provenance slice", which combines a data slice and a program slice to yield insights into the cause-effect relations among system behaviors. To cope with the large volume of fine-grained provenance traces, we propose use-inspired filters to reduce the amount of provenance, and a provenance slicing technique called "non-preprocessing provenance slicing" that directly queries over provenance traces without recovering all provenance entities and dependencies beforehand. We evaluate performance and utility using a well known ecological NetLogo model called "wolf-sheep- predation".

AB - Researchers who use agent-based models (ABM) to model social patterns often focus on the model's aggregate phenomena. However, aggregation of individuals complicates the understanding of agent interactions and the uniqueness of individuals. We develop a method for tracing and capturing the provenance of individuals and their interactions in the NetLogo ABM, and from this create a "dependency provenance slice", which combines a data slice and a program slice to yield insights into the cause-effect relations among system behaviors. To cope with the large volume of fine-grained provenance traces, we propose use-inspired filters to reduce the amount of provenance, and a provenance slicing technique called "non-preprocessing provenance slicing" that directly queries over provenance traces without recovering all provenance entities and dependencies beforehand. We evaluate performance and utility using a well known ecological NetLogo model called "wolf-sheep- predation".

UR - http://www.scopus.com/inward/record.url?scp=84893483137&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84893483137&partnerID=8YFLogxK

U2 - 10.1109/eScience.2013.39

DO - 10.1109/eScience.2013.39

M3 - Conference contribution

AN - SCOPUS:84893483137

SN - 9780768550831

T3 - Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013

SP - 180

EP - 187

BT - Proceedings - IEEE 9th International Conference on e-Science, e-Science 2013

PB - IEEE Computer Society

ER -