A standard form of citation of this article is:
Harbers, Maaike, Meyer, John-Jules and van den Bosch, Karel (). 'Explaining Simulations Through Self Explaining Agents'. Journal of Artificial Societies and Social Simulation 12(3)6 <https://www.jasss.org/12/3/6.html>.
The following can be copied and pasted into a Bibtex bibliography file, for use with the LaTeX text processor:
@article{harbers,
title = {Explaining Simulations Through Self Explaining Agents},
author = {Harbers, Maaike and Meyer, John-Jules and van den Bosch, Karel},
journal = {Journal of Artificial Societies and Social Simulation},
ISSN = {1460-7425},
volume = {12},
number = {3},
pages = {6},
year = {},
URL = {https://www.jasss.org/12/3/6.html},
keywords = {Explanation, Agents, Goal-Based Behavior, Virtual Training},
abstract = {Several strategies are used to explain emergent interaction patterns in agent-based simulations. A distinction can be made between simulations in which the agents just behave in a reactive way, and simulations involving agents with also pro-active (goal-directed) behavior. Pro-active behavior is more variable and harder to predict than reactive behavior, and therefore it might be harder to explain. However, the approach presented in this paper tries to make advantage of the agents' pro-activeness by using it to explain their behavior. The aggregation of the agents' explanations form a basis for explaining the simulation as a whole. In this paper, an agent model that is able to generate (pro-active) behavior and explanations about that behavior is introduced, and the implementation of the model is discussed. Examples show how the link between behavior generation and explanation in the model can contribute to the explanation of a simulation.},
}The following can be copied and pasted into a text file, which can then be imported into a reference database that supports imports using the RIS format, such as Reference Manager and EndNote.
TY - JOUR
TI - Explaining Simulations Through Self Explaining Agents
AU - Harbers, Maaike
AU - Meyer, John-Jules
AU - van den Bosch, Karel
Y1 -
JO - Journal of Artificial Societies and Social Simulation
SN - 1460-7425
VL - 12
IS - 3
SP - 6
UR - https://www.jasss.org/12/3/6.html
KW - Explanation
KW - Agents
KW - Goal-Based Behavior
KW - Virtual Training
N2 - Several strategies are used to explain emergent interaction patterns in agent-based simulations. A distinction can be made between simulations in which the agents just behave in a reactive way, and simulations involving agents with also pro-active (goal-directed) behavior. Pro-active behavior is more variable and harder to predict than reactive behavior, and therefore it might be harder to explain. However, the approach presented in this paper tries to make advantage of the agents' pro-activeness by using it to explain their behavior. The aggregation of the agents' explanations form a basis for explaining the simulation as a whole. In this paper, an agent model that is able to generate (pro-active) behavior and explanations about that behavior is introduced, and the implementation of the model is discussed. Examples show how the link between behavior generation and explanation in the model can contribute to the explanation of a simulation.
ER -