Learning Brave Assumption-Based Argumentation Frameworks via ASP

Assumption-based Argumentation (ABA) frameworks havebeen advocated as unifying frameworks for various forms of non-monotonicreasoning, including logic programming. In recent work we have pre-sented an approach for learning ABA frameworks from background knowl-edge and positive and negative examples. Our approach is based on theuse of transformation rules, including some adapted from logic programtransformation rules (notably folding) as well as new, specific ones, suchas rote learning and assumption introduction. In this paper we addressthe problem of automating the learning of ABA frameworks in the casewhere acceptance is defined in terms of brave reasoning under stable ex-tensions. We present an algorithm for applying the transformation rulesand its implementation that makes use of Answer Set Programming