Citation

BibTex format

@inproceedings{Irwin:2022,
author = {Irwin, B and Rago, A and Toni, F},
publisher = {IJCAI Organisation},
title = {Forecasting argumentation frameworks},
url = {http://hdl.handle.net/10044/1/97080},
year = {2022}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - We introduce Forecasting Argumentation Frameworks(FAFs), a novel argumentation-based methodology forforecasting informed by recent judgmental forecastingresearch. FAFs comprise update frameworks which empower(human or artificial) agents to argue over time about theprobability of outcomes, e.g. the winner of a politicalelection or a fluctuation in inflation rates, whilst flaggingperceived irrationality in the agents’ behaviour with a viewto improving their forecasting accuracy. FAFs include fiveargument types, amounting to standard pro/con arguments,as in bipolar argumentation, as well as novel proposalarguments and increase/decrease amendment arguments. Weadapt an existing gradual semantics for bipolar argumen-tation to determine the aggregated dialectical strength ofproposal arguments and define irrational behaviour. We thengive a simple aggregation function which produces a finalgroup forecast from rational agents’ individual forecasts.We identify and study properties of FAFs and conductan empirical evaluation which signals FAFs’ potential toincrease the forecasting accuracy of participants.
AU - Irwin,B
AU - Rago,A
AU - Toni,F
PB - IJCAI Organisation
PY - 2022///
SN - 2334-1033
TI - Forecasting argumentation frameworks
UR - http://hdl.handle.net/10044/1/97080
ER -