Culturally Aware Social Robots That Carry Humans Inside Them, Protected by Defeasible Argumentation Systems

After taking note of the conceptual fact that robots may well carry humans inside them, and more specifically that modern AI-infused cars, jets, spaceships, etc. can be viewed as such robots, we present a case study in which inconsistent attitude measurements resulted in the tragic crash in Sweden of such a jet and the death of both pilots. After setting out desiderata for an automated defeasible inductive reasoner able to suitably prevent such tragedies, we formalize the scenario in a first-order defeasible reasoner—OSCAR—and find that it can quickly generate a partial solution to the dilemma the pilots couldn’t conquer. But we then note and address the shortcomings of OSCAR relative to the desiderata, and adumbrate a solution supplied by a more expressive reasoner based on an inductive defeasible multi-operator cognitive calculus (ℐ𝒟𝒞ℰ𝒞) that is inspired by a merely deductive (monotonic) precursor (𝒟𝒞ℰ𝒞). Our solution in this calculus exploits both the social and cultural aspects of of the jet/robot we suggest be engineered in the future. After describing our solution, some remarks about related prior work follow, we present and rebut two objections, and then wrap up with a brief conclusion.

Ranking Semantics for Argumentation Systems With Necessities

Bipolar argumentation studies argumentation graphs where attacks are combined with another relation between arguments. Many kind of relations (e.g. deductive support, evidential support, necessities etc.) have been defined and investigated from a Dung semantics perspective. We place ourselves in the context of argumentation systems with necessities and provide the first study to investigate ranking semantics in this setting. To this end, we (1) provide a set of postulates specifically designed for necessities and (2) propose the first ranking-based semantics in the literature to be shown to respect these postulates.

Two Sides of the Same Coin: Belief Revision and Enforcing Arguments

We study a type of change on knowledge bases inspired by the dynamics of formal argumentation systems, where the goal is to enforce acceptance of certain arguments. We put forward that enforcing acceptance of arguments can be viewed as a member of the wider family of belief change operations, and that an axiomatic treatment of it is therefore desirable. In our case, laying down axioms enables a precise account of the close connection between enforcing arguments and belief revision. Our analysis of enforcing arguments proceeds by (i) axiomatizing it as an operation in propositional logic and providing a representation result in terms of rankings on sets of interpretations, (ii) showing that it stands in close relationship to belief revision, and (iii) using it as a gateway towards a principled treatment of enforcement in abstract argumentation.

Relevance in Structured Argumentation

We study properties related to relevance in non-monotonic consequence relations obtained by systems of structured argumentation. Relevance desiderata concern the robustness of a consequence relation under the addition of irrelevant information. For an account of what (ir)relevance amounts to we use syntactic and semantic considerations. Syntactic criteria have been proposed in the domain of relevance logic and were recently used in argumentation theory under the names of non-interference and crash-resistance. The basic idea is that the conclusions of a given argumentative theory should be robust under adding information that shares no propositional variables with the original database. Some semantic relevance criteria are known from non-monotonic logic. For instance, cautious monotony states that if we obtain certain conclusions from an argumentation theory, we may expect to still obtain the same conclusions if we add some of them to the given database. In this paper we investigate properties of structured argumentation systems that warrant relevance desiderata.

Dynamics of Argumentation Systems: A Basic Theory

The changing of arguments and their attack relation is an intrinsic property of a variety of argumentation systems. So, it is very important to efficiently figure out how the status of arguments in a system evolves when the system is updated. However, unlike other areas of argumentation that have been deeply explored, such as argumentation semantics, proof theories, and algorithms, etc., dynamics of argumentation systems has been comparatively neglected. In this paper, we introduce a general theory (called a division-based method) to cope with this problem based on a new concept: the division of an argumentation framework. When an argumentation framework is updated, it is divided into three parts: an unaffected, an affected, and a conditioning part. The status of arguments in the unaffected sub-framework remains unchanged, while the status of the affected arguments is computed in a special argumentation framework (called a conditioned argumentation framework, or briefly CAF) that is composed of an affected part and a conditioning part. We have proved that under a certain semantics that satisfies the directionality criterion (complete, preferred, ideal, or grounded semantics), the extensions of the updated framework are equal to the result of a combination of the extensions of an unaffected sub-framework and sets of the extensions of a set of assigned CAFs. The theory shows that the complexity of computing the dynamics of argumentation will decrease to a lesser or greater extent, depending on the types of argumentation semantics, the topologies of argumentation frameworks, and the number of affected arguments with respect to an addition or a deletion. As a result, this theory is expected to be very useful in various kinds of argumentation systems where arguments and attacks are dynamics, due to the changing of underlying knowledge and information.

An Efficient Java-Based Solver for Abstract Argumentation Frameworks: jArgSemSAT

Dung’s argumentation frameworks are adopted in a variety of applications, from argument-mining, to intelligence analysis and legal reasoning. Despite this broad spectrum of already existing applications, the mostly adopted solver—in virtue of its simplicity—is far from being comparable to the current state-of-the-art solvers. On the other hand, most of the current state-of-the-art solvers are far too complicated to be deployed in real-world settings. In this paper we provide and extensive description of jArgSemSAT, a Java re-implementation of ArgSemSAT. ArgSemSAT represents the best single solver for argumentation semantics with the highest level of computational complexity. We show that jArgSemSAT can be easily integrated in existing argumentation systems (1) as an off-the-shelf, standalone, library; (2) as a Tweety compatible library; and (3) as a fast and robust web service freely available on the Web. Our large experimental analysis shows that despite being written in Java, jArgSemSAT would have scored in most of the cases among the three bests solvers for the two semantics with highest computational complexity “Stable and Preferred” in the last competition on computational models of argumentation.