In enthymeme-based dialogues, involved participants create assumptions in order to decode arguments from the exchanged enthymemes. This work introduces the concept of assumptions operator, which formalizes the mechanism for generating these assumptions, and proposes a set of principles to guide the construction of these operators. Said principles are inspired by Grice’s Maxims of Conversation, as well as Govier’s ARG conditions for cogent arguments. Then, in order to analyze how the used operator influences the dialogue and how that dialogue differs from the one in which the original argument is sent, we propose a framework to compare both scenarios, the former being the enthymemic one and the latter the complete one. Finally, we formally show that if the used assumptions operator complies with a set of the aforementioned principles, then most arguments in the complete dialogue have their counterpart in the enthymemic one. Furthermore, we show that under certain conditions, the enthymemic dialogue preserves some semantic properties from the complete one, specifically: conflict-freeness, acceptability and admissibility.

Arguments in argumentation systems cannot always be considered as standalone entities, requiring the consideration of the pieces of evidence they rely on. This evidence might have to be retrieved from external sources such as databases or the web, and each attempt to retrieve a piece of evidence comes with an associated cost. Moreover, a piece of evidence may be available in a given scenario but not in others, and this is not known beforehand. As a result, the collection of active arguments (whose entire set of evidence is available) that can be used by the argumentation machinery of the system may vary from one scenario to another. In this work, we consider an Abstract Argumentation Framework with Fallible Evidence that accounts for these issues, and propose a heuristic measure used as part of the acceptability calculus (specifically, for building pruned dialectical trees) with the aim of minimizing the evidence retrieval cost of the arguments involved in the reasoning process. We provide an algorithmic solution that is empirically tested against two baselines and formally show the correctness of our approach.

Abstract This paper formally compares some central notions from two well-known formalisms for rule-based argumentation, DeLP and ASPIC+. The comparisons especially focus on intuitive adequacy and inter-translatability, consistency, and closure properties. As for differences in the definitions of arguments and attack, it turns out that DeLP’s definitions are intuitively appealing but that they may not fully comply with Caminada and Amgoud’s rationality postulates of strict closure and indirect consistency. For some special cases, the DeLP definitions are shown to fare better than ASPIC+. Next, it is argued that there are reasons to consider a variant of DeLP with grounded semantics, since in some examples its current notion of warrant arguably has counterintuitive consequences and may lead to sets of warranted arguments that are not admissible. Finally, under some minimality and consistency assumptions on ASPIC+ arguments, a one-to-many correspondence between ASPIC+ arguments and DeLP arguments is identified in such a way that if the DeLP warranting procedure is changed to grounded semantics, then ’s DeLP notion of warrant and ASPIC+ ’s notion of justification are equivalent. This result is proven for three alternative definitions of attack.

The Attack-Support Argumentation Framework (ASAF) is an abstract argumentation framework that provides a unified setting for representing attack and support for arguments, as well as attack and support for the attack and support relations at any level. Currently, the extensions of the ASAF are obtained by translating it into a Dung's Argumentation Framework (AF). In this work we provide the ASAF with the ability of determining its extensions without requiring such a translation. We follow an extension-based approach for characterizing the acceptability semantics directly on the ASAF, considering the complete, preferred, stable and grounded semantics. Finally, we show that the proposed characterization satisfies different results from Dung's argumentation theory.

The development of symbolic approaches to decision-making has become an ever-growing research line in artificial intelligence; argumentation has contributed to that with its unique strengths. Following this trend, this article proposes a general-purpose decision framework based on argumentation. Given a set of alternatives posed to the decision-maker, the framework represents the agent's preferences and knowledge by an epistemic component developed using possibilistic defeasible logic programming. The reasons by which a particular alternative is deemed better than another are explicitly considered in the argumentation process involved in warranting information from the epistemic component. The information warranted by the dialectical process is then used in decision rules that implement the agent's general decision-making policy. Essentially, decision rules establish patterns of behaviour of the agent specifying under which conditions a set of alternatives will be considered acceptable; moreover, a methodology for programming the agent's epistemic component is defined. It is demonstrated that programming the agent's epistemic component following this methodology exhibits some interesting properties with respect to the selected alternatives; also, when all the relevant information regarding the agent's preferences is specified, its choice behaviour coincides with respect to the optimum preference derived from a rational preference relation.

Abstract This article is devoted to the study of methods to change defeasible logic programs (de.l.p.s) which are the knowledge bases used by the Defeasible Logic Programming (DeLP) interpreter. DeLP is an argumentation formalism that allows to reason over potentially inconsistent de.l.p.s. Argument Theory Change (ATC) studies certain aspects of belief revision in order to make them suitable for abstract argumentation systems. In this article, abstract arguments are rendered concrete by using the particular rule-based defeasible logic adopted by DeLP. The objective of our proposal is to define prioritized argument revision operators à la ATC for de.l.p.s, in such a way that the newly inserted argument ends up undefeated after the revision, thus warranting its conclusion. In order to ensure this warrant, the de.l.p. has to be changed in concordance with a minimal change principle. To this end, we discuss different minimal change criteria that could be adopted. Finally, an algorithm is presented, implementing the argument revision operations.

In this work we introduce an extension of an structured argumentation system in which presumptions are fully integrated in the reasoning mechanism. A presumption is defined as a piece of information that is tentatively taken to be true, usually in the absence of acceptable reasons to the contrary. In Presumptive Defeasible Logic Programming (PreDeLP), arguments can be built from both facts and presumptions. We analyze several criteria to compare arguments in PreDeLP, and highlight one possibility that captures the semantic difference between presumptions and facts or defeasible rules. On top of PreDeLP we develop a defeasible approach to argumentation-based diagnostic reasoning. The use of presumptions permits to extend the reasoning beyond factual information, creating in this way a universe of possible scenarios that support or interfere with a claim. We characterize the set of possible scenarios for and against a claim and identify those that best explain the warrant status of the query.

In abstract frameworks with varied strength attacks (AFV), arguments may attack each other with different strength. An admissible scenario is an admissible set of arguments fulfilling certain strength conditions about defences. In this work we analyze the computational complexity of some decision problems related to the quality of admissible scenarios: checking the property of being top-admissible and the property of being equilibrated. These problems are implying an exhaustive comparison between scenarios, and both of them are shown to be coNP-complete.

Argument Theory Change (ATC) applies classic belief change concepts to the area of argumentation. This intersection of fields takes advantage of the definition of a Dynamic Abstract Argumentation Framework, in which an argument is either active or inactive, and only in the former case it is taken into consideration in the reasoning process. ATC identifies how the framework has to be modified in order to achieve warrant for a certain argument. The present article copes with this matter by defining a revision operator based on activation of arguments, i.e., recognizing the knowledge that is missing.

This article introduces the notion of dynamics for abstract argumentation frameworks. We consider evidence as the basis from which arguments may be considered valid. The proposed Dynamic Argumentation Framework (DAF) is a refinement of Dung's abstract framework (AF), enriched with additional features. Since an instance of a DAF is equivalent to an AF, the former could be viewed as a template to build different AFs, applying the same knowledge to different situations. This equivalence is important, as we can take advantage of the vast amount of study on argumentation semantics for AFs to apply it to our approach. The DAF's aim is to provide a well-structured knowledge representation tool that allows for the definition of dynamics-aware argumentation-based systems.

The work reported here introduces Defeasible Logic Programming (DeLP), a formalism that combines results of Logic Programming and Defeasible Argumentation. DeLP provides the possibility of representing information in the form of weak rules in a declarative manner, and a defeasible argumentation inference mechanism for warranting the entailed conclusions. In DeLP an argumentation formalism will be used for deciding between contradictory goals. Queries will be supported by arguments that could be defeated by other arguments. A query $q$ will succeed when there is an argument ${\mathcal A}$ for $q$ that is warranted, i.e. the argument ${\mathcal A}$ that supports $q$ is found undefeated by a warrant procedure that implements a dialectical analysis. The defeasible argumentation basis of DeLP allows to build applications that deal with incomplete and contradictory information in dynamic domains. Thus, the resulting approach is suitable for representing agent's knowledge and for providing an argumentation based reasoning mechanism to agents.