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 DO - kr.2022/55 EP - 543 PB - IJCAI Organisation PY - 2022/// SN - 2334-1033 SP - 533 TI - Forecasting argumentation frameworks UR - http://dx.doi.org/10.24963/kr.2022/55 UR - https://proceedings.kr.org/2022/55/ UR - http://hdl.handle.net/10044/1/97080 ER -