On monotonicity of dispute trees as explanations for case-based reasoning with abstract argumentation

Recent work on explainability raises the question of what different types of explanations actually mean. One idea is that explanations can reveal information about the behaviour of the model on a subset of the input space. When this way of interpreting explanations is thought as an interactive process, inferences from explanations can be seen as a form of reasoning. In the case of case-based reasoning with abstract argumentation (AA-CBR), previous work has used arbitrated dispute trees as a methodology for explanation. Those are dispute trees where nodes are seen as losing or winning depending on the outcome for the new case under consideration. In this work we show how arbitrated dispute trees can be readapted for different inputs, which allows a broader interpretation of them, capturing more of the input-output behaviour of the model. We show this readaptation is correct by construction, and thus the resulting reasoning based on this reuse is monotonic and thus necessarily a faithful explanation.