Assumption-based Argumentation (ABA) is advocated as a unifying formalism for various forms of non-monotonic reasoning, including logic programming. It allows capturing defeasible knowledge, subject to argumentative debate. While, in much existing work, ABA frameworks are given up-front, in this paper we focus on the problem of automating their learning from background knowledge and positive/negative examples. Unlike prior work, we newly frame the problem in terms of brave reasoning under stable extensions for ABA. We present a novel algorithm based on transformation rules (such as Rote Learning, Folding, Assumption Introduction and Fact Subsumption) and an implementation thereof that makes use of Answer Set Programming. Finally, we compare our technique to state-of-the-art ILP systems that learn defeasible knowledge.

Quaker has a new robot chef and her name is Alexa. The 135-year-old maker of oats is harnessing the power of artificial intelligence to help consumers make an oatmeal method as old as Quaker itself: overnight oats. Working with agency partner Organic, Quaker has built its first ever app for Amazon's virtual assistant, which is available through products like the Echo speaker. The app, which debuted on Sunday at South by Southwest in Austin, Texas, helps users find and make recipes for overnight oats, a trend that came as a bit of a surprise to the household brand that arguably knows oatmeal better than anyone. The idea for the app began a few months ago, after Quaker's social media team noticed there was a resurgence of an age-old tradition of cooking oats the night before and then letting them cool in the refrigerator overnight to be eaten cold the next morning.