In this section
@article{Kampik:2024:10.1016/j.ijar.2024.109255,
author = {Kampik, T and Potyka, N and Yin, X and yras, K and Toni, F},
doi = {10.1016/j.ijar.2024.109255},
journal = {International Journal of Approximate Reasoning},
title = {Contribution functions for quantitative bipolar argumentation graphs: a principle-based analysis},
url = {http://dx.doi.org/10.1016/j.ijar.2024.109255},
volume = {173},
year = {2024}
}
TY - JOUR
AB - We present a principle-based analysis of contribution functions for quantitative bipolar argumentation graphs that quantify the contribution of one argument to another. The introduced principles formalise the intuitions underlying different contribution functions as well as expectations one would have regarding the behaviour of contribution functions in general. As none of the covered contribution functions satisfies all principles, our analysis can serve as a tool that enables the selection of the most suitable function based on the requirements of a given use case.
AU - Kampik,T
AU - Potyka,N
AU - Yin,X
AU - yras,K
AU - Toni,F
DO - 10.1016/j.ijar.2024.109255
PY - 2024///
SN - 0888-613X
TI - Contribution functions for quantitative bipolar argumentation graphs: a principle-based analysis
T2 - International Journal of Approximate Reasoning
UR - http://dx.doi.org/10.1016/j.ijar.2024.109255
UR - http://hdl.handle.net/10044/1/113576
VL - 173
ER -
Artificial Intelligence Network
South Kensington Campus
Imperial College London
SW7 2AZ
To reach the elected speaker of the network, Dr Rossella Arcucci, please contact:
To reach the network manager, Diana O'Malley - including to join the network - please contact: