In this paper, we introduce novel methods for drawing conclusions from inconsistent information in a highly cautious manner. While standard paraconsistent approaches typically rely on the formulas in the intersection of maximally consistent subsets, known as the free formulas, we argue that not all these formulas share the same degree of reliability. Our refined reasoning frameworks distinguish between free formulas, based on their actual involvement in the inconsistency, an so enabling inference only when conclusions are robustly supported. These methods are particularly valuable in high-stakes contexts where decisions carry irreversible or far-reaching consequences. We present several implementation techniques grounded in multi-valued semantics and syntactic independence, analyze their fundamental logical properties, and establish a hierarchy of their inferential strength.

Inconsistency measures quantify the degree of conflict within a set of propositions. They can be broadly categorized into global measures, which assess the overall inconsistency of a set, and local measures, which evaluate the contribution of single formulas to the overall inconsistency. This paper investigates the relationship between these two classes of measures through the lens of marginal contributions and pooling mechanisms. We propose a systematic framework for deriving local inconsistency measures from global ones by employing notions of marginal contributions inspired by cooperative game theory, including Shapley and Banzhaf values. Conversely, we explore methods for constructing global inconsistency measures by aggregating local contributions using various pooling techniques. A key research question arises: which combinations of marginal contribution notions (maC) and pooling mechanisms (P) are compatible? Compatibility is defined such that, given a global measure I, applying (P) to the marginal contributions derived from I yields the same result as directly applying I, and vice versa. We analyze this compatibility condition and identify specific pairs of methods, (maC) and (P), that satisfy it across various inconsistency frameworks. Our findings provide a deeper understanding of the interplay between global and local inconsistency measures, providing a foundation for designing principled and interpretable inconsistency evaluation methods in logic-based systems.

Logic-based argumentation is a formal method for constructing, evaluating and comparing arguments. In this paper we address two (related) key issues concerning the representation of logical argumentation frameworks: how to describe them in a compact way, and how to move from one framework to another while preserving their basic logical characteristics. The results are applied to various forms of attack rules and different kinds of argumentative semantics, and are demonstrated for transitions between several 3-valued logics and classical logic. As a byproduct, our results are also used for converting logic-based argumentation frameworks to assumption-based argumentation frameworks.

We present a novel computational approach to resolving conflicts among norms by nonmonotonic normative reasoning (in constrained I/O logics). Our approach extends standard sequent-based proof systems and makes them more adequate to nonmonotonic reasoning by adding to the sequents annotations that keep track of what is known about the defeasible status of the derived sequents. This makes transparent the reasons according to which norms should be applicable or inapplicable, and accordingly the sequents that make use of such norms are accepted or retracted. We also show that this proof theoretic method has tight links to the semantics of formal argumentation frameworks. The outcome of this paper is thus a threefold characterization result that relates, in the context of nonmonotonic normative reasoning, three traditional ingredients of AI-based reasoning methods: maximally consistent sets of premises (in constrained I/O logics), derived sequents (which are accepted in corresponding annotated sequent calculi), and logical arguments (that belong to the grounded extensions of the induced logical argumentation frameworks).

We propose a novel knowledge representation method for the Default Logic paradigm by developing a proof calculus that yields arguments and counter-arguments in which defaults serve as explicit objects of reasoning. The proposed formalism allows for more transparent default reasoning and the use of explain-ability methods in formal argumentation. In particular, we provide a sound and complete argumentative characterization of Default Logic, by demonstrating that argumentation frameworks instantiated by the arguments derivable in our calculus yields the same inference relation as that of Default Logic. The modularity of our approach allows for various modifications of Default Logic. We demonstrate this by extending our calculus with a rule that enables disjunctive defeasible reasoning.

Conflicts are inherent to normative systems. In this paper, we explore a novel approach to normative reasoning by quantifying the amount of conflicts within normative systems. We refine the idea from classical logic, according to which a formula is a consequence of a knowledge base in case its negation renders the knowledge base inconsistent. In our approach, whether a formula is a logical consequence depends, for instance, on its negation's marginal contribution to the inconsistency of the given knowledge base. Accordingly, various inconsistency measures and corresponding (nonmonotonic and paraconsistent) normative entailment relations are analyzed relative to a number of logical properties. To illustrate our approach, we adopt Input/Output logic, a renowned formalism in deontic logic, specifically designed for defeasible normative reasoning. As an application, the resulting entailment relations provide recommendations to agents for minimizing norm conflicts, and may be incorporated in a number of implementations (like the Tweety libraries and the LogiKey framework) by involving inconsistency measurements in normative reasoning.

Recent studies have focused on autonomous agents that select their own goals and then select actions to achieve these goals, using online Goal Reasoning (GR). GR agents can revise goals and plans at execution time if unexpected outcomes occur. However, for ethical or legal agent design, even the partial execution of an online plan may result in foreseeable norm violations. To prevent these violations, it is crucial to incorporate GR already at the planning phase. To this end, we design an offline GR system that can harbour normative systems or deontic logics for goal generation. Our main results include a characterization and comparison of the completeness classes for a variety of offline GR planners, and a discussion of the irreducibility of offline GR to pure planning methods.

Abstract Default logic and formal argumentation are paradigmatic methods in the study of nonmonotonic inference. Defeasible information often comes in different strengths stemming from different degrees of reliability in epistemic applications or from varying strengths of authorities issuing norms in deontic applications. In both paradigms, methods have been developed to deal with prioritized knowledge bases and normative systems. Questions of comparability of these methods therefore naturally arise. Argumentation theory has been developed with a strong emphasis on unification. It is therefore a desideratum to obtain natural representations of various approaches to (prioritized) default logic within frameworks of structured argumentation, such as ASPIC. Important steps in this direction have been presented in Liao et al. (2016, 2018). In this work, we identify and address some problems in earlier translations, we broaden the focus from total to modular orderings of defaults and we consider non-normal defaults.

In formal argumentation, a distinction can be made between extension-based semantics, where sets of arguments are either (jointly) accepted or not, and ranking-based semantics, where grades of accept- ability are assigned to arguments. Another important distinction is that between abstract approaches, that abstract away from the content of arguments, and structured approaches, that specify a method of constructing argument graphs on the basis of a knowledge base. While ranking-based semantics have been extensively applied to abstract argumentation, few work has been done on ranking-based semantics for structured argumentation. In this paper, we make a systematic investigation into the be- haviour of ranking-based semantics applied to existing formalisms for structured argumentation. We show that a wide class of ranking-based semantics gives rise to so-called culpability measures, and are relatively robust to specific choices in argument construction methods.

Ranking is ubiquitous in everyday life. This paper is concerned with the problem of ranking information of a knowledge base when this latter is possibly inconsistent. In particular, the key issue is to elicit a plausibility order on the formulas in an inconsistent knowledge base. We show how such ordering can be obtained by using only the inherent structure of the knowledge base. We start by introducing a principled way a reasonable ranking framework for formulas should satisfy. Then, a variety of ordering criteria have been explored to define plausibility order over formulas based on consistency. Finally, we study the behaviour of the different formula ranking semantics in terms of the proposed logical postulates as well as their (in)-compatibility.

This paper presents a formal model of specific reasoning patterns in conflict of laws (CoL). CoL arises when multiple countries have jurisdiction due to the diverse nationalities of the involved factors. When initiating legal action in one country, the question of which country’s substantial law to apply emerges, possibly involving the CoL regulations of other countries (in cases of transmission and renvoi). Moreover, parties contemplating legal action in a case falling under CoL often engage in a deliberation process known as forum shopping: determining which country’s CoL regulations would result in the most favorable outcome for them. Our model integrates deontic logic (specifically Input/Output logic) with proof theory and formal argumentation techniques to model both types of reasoning.

Logical argumentation is a well-known approach to modeling non-monotonic reasoning with conflicting information. In this paper we provide a comprehensive postulate-based study of properties of logical argumentation frameworks and a full characterization of their semantics and inference relations. In this way we identify well-behaved formal argumentative models of drawing logically justified inferences from a given set of possibly conflicting defeasible, as well as strict assumptions. Given some desiderata in terms of rationality postulates, we consider the conditions that an argumentation framework should fulfill for the desiderata to hold. One purpose of this approach is to assist designers to “plug-in” pre-defined formalisms according to actual needs. To this end, we present a classification of argumentation frameworks relative to the types of attacks they implement. In turn, for each class we determine which desiderata are satisfied. Our study is highly abstract, supposing only a minimal set of requirements on the considered underlying deductive systems, and in this way covering a broad range of formalisms, including classical, intuitionistic and modal logics.

Normative reasoning is inherently defeasible. Formal argumentation has proven to be a unifying framework for representing nonmonotonic logics. In this work, we provide an argumentative characterization of a large class of Input/Output logics, a prominent defeasible formalism for normative reasoning. In many normative reasoning contexts, one is not merely interested in knowing whether a specific obligation holds, but also in why it holds despite other norms to the contrary. We propose sequent-style argumentation systems called Deontic Argument Calculi (DAC), which serve transparency and bring meta-reasoning about the inapplicability of norms to the object language level. We prove soundness and completeness between DAC-instantiated argumentation frameworks and constrained Input/Output logics. We illustrate our approach in view of two deontic paradoxes.

Explainable artificial intelligence (XAI) has gained increasing interest in recent years in the argumentation community. In this paper we consider this topic in the context of logic-based argumentation, showing that the latter is a particularly promising paradigm for facilitating explainable AI. In particular, we provide two representations of abductive reasoning by sequent-based argumentation frameworks and show that such frameworks successfully cope with related challenges, such as the handling of synonyms, justifications, and logical equivalences.

We introduce annotated sequent calculi, which are extensions of standard sequent calculi, where sequents are combined with annotations that represent their derivation statuses. Unlike in ordinary calculi, sequents that are derived in annotated calculi may still be retracted in the presence of conflicting sequents, thus inferences are made under stricter conditions. Conflicts in the resulting systems are handled like in adaptive logics and argumentation theory. The outcome is a robust family of proof systems for non-monotonic reasoning with inconsistent information, where revision considerations are fully integrated into the object level of the proofs. These systems are shown to be strongly connected to logical argumentation.

In this paper we provide a detailed analysis of the inference process induced by logical argumentation frameworks. The frameworks may be defined with respect to any propositional language and logic, different arguments that represent deductions in the logic, various support-based attack relations between arguments, and all the complete Dung-style semantics for the frameworks. We show that, ultimately, for characterizing the inference process with respect to a given framework, extension-based semantics may be divided into two types: single-extension and multiple-extension, which induce respective kinds of entailment relations. These entailments are further classified by the way they tolerate new information (nonmonotonicity-related properties) and maintain conflicts among arguments (inconsistency-related properties).

We present a formal argumentation system for dealing with the detachment of prioritized conditional obligations and permissions. In the presence of facts and constraints, we answer the question whether an unconditional obligation or permission is detachable by considering arguments for and against its detachment. For the evaluation of arguments in favour of detachment, we use a Dung-style argumentation-theoretical semantics. We illustrate how violations and contrary-to-duty scenarios are dealt with in our framework and pay special attention to conflict-resolution via priorities.

In this article, we present an argumentative approach to normative reasoning. Special attention is paid to deontic conflicts, contrary-to-duty and specificity cases, which are modelled by means of argumentative attacks. For this, we adopt a recently proposed framework for logical argumentation in which arguments are generated by a sequent calculus of a given base logic (see the papers of the second author in CLIMA'2013 and of the two authors in Volume 6 (No. 1) of Argument & Computation ), and use standard deontic logic as our base logic. Argumentative attacks are realized by elimination rules that allow to discharge specific sequents. We demonstrate the usefulness of our approach by means of various well-known benchmark examples, and show that this approach is rich enough to capture a variety of paradigms for handling conflicting norms such as reasoning with maximally consistent sets, prioritized norms and deontic formalisms based on I/O logic.

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.

Reasoning with the maximally consistent subsets (MCS) of the premises is a well-known approach for handling contradictory information. In this paper we consider several variations of this kind of reasoning, for each one we introduce two complementary computational methods that are based on logical argumentation theory. The difference between the two approaches is in their ways of making consequences: one approach is of a declarative nature and is related to Dung-style semantics for abstract argumentation, while the other approach has a more proof-theoretical flavor, extending Gentzen-style sequent calculi. The outcome of this work is a new perspective on reasoning with MCS, which shows a strong link between the latter and argumentation systems, and which can be generalized to some related formalisms. As a by-product of this we obtain soundness and completeness results for the dynamic proof systems with respect to several of Dung’s semantics. In a broader context, we believe that this work helps to better understand and evaluate the role of logic-based instantiations of argumentation frameworks.

In structured argumentation frameworks such as ASPIC+, rebuts are only allowed in conclusions produced by defeasible rules. This has been criticized as counter-intuitive especially in dialectical contexts. In this paper we show that ASPIC-, a system allowing for unrestricted rebuts, suffers from contamination problems. We remedy this shortcoming by generalizing the attack rule of unrestricted rebut. Our resulting system satisfies the usual rationality postulates for prioritized rule bases.

In the context of non-monotonic reasoning different kinds of consequence relations are defined for reasoning from (possibly) inconsistent information. Examples are consequence relations that are characterized in terms of maximal consistent subsets of the premise set. The strong consequences are those formulas that follow by Classical Logic from every maximal consistent subset. The weak consequences follow from some maximal consistent subset. The free consequences follow from the set of formulas that belong to every maximal consistent subset. In this paper the question is discussed which of these consequence relations should be applied in which reasoning context. First the concerns that are expressed in the literature with respect to the usefulness of the weak consequences are addressed. Then it is argued that making weak inferences is sensible for some application contexts, provided one has a (dynamic) proof theory for the corresponding consequence relation. Such a dynamic proof theory is what adaptive logics offer. Finally, all this is illustrated by means of a very simple adaptive logic reconstruction of the free, strong, and weak consequences.

The standard format of adaptive logics makes use of two so-called strategies: reliability and minimal abnormality.While these are fairly well-known and frequently applied, the question of whether and when the two strategies are equi-epressive has so far remained unaddressed.In this paper, we show that for a specific, yet significant class of premise sets, the consequence set of an adaptive logic that uses the minimal abnormality strategy can be expressed by another adaptive logic that uses the reliability strategy.The basic idea is that we close the set of abnormalities under conjunction.We show that the consequence sets obtained by both logics from a premise set Γ is identical if and only if Γ is finite-conditional.The latter property is specified in terms of a well-known characterization of minimal abnormality.In addition, we discuss other (stronger) properties of premise sets that have been considered in the literature, showing each of them to imply finite-conditionality.

We introduce a reactive variant of SDL (standard deontic logic): SDLR1 (reactive standard deontic logic). Given a Kripkean view on the semantics of SDL in terms of directed graphs where arrows → represent the accessibility relation between worlds, reactive models add two elements: arrows → are labelled as ‘active’ or ‘inactive’, and double arrows ↠ connect arrows, e.g. (x1 → x2) ↠ (x3 → x4). The idea is that passing through x1 → x2 activates a switch represented by ↠ that inverts the label of x3 → x4 and hence activates respectively deactivates this arrow. This allows to introduce two modalities: □ is the usual KD-modality of SDL and operates on the Kripkean graph where all labels and double arrows are ignored, while Ø takes them into account. We demonstrate that RSDL1 allows for an intuitive interpretation of ‘ought’. The logic can handle contrary-to-duty cases such as several instantiations of the Chisholm set in a paradox-free way by means of using double arrows and annotations to block and give access to ideal worlds.

We introduce a general approach for representing and reasoning with argumentation-based systems. In our framework arguments are represented by Gentzen-style sequents, attacks (conflicts) between arguments are represented by sequent elimination rules, and deductions are made by dynamic proof systems. This framework accommodates different languages and logics in which arguments may be represented, supports a variety of attack relations, and tolerates dynamic changes in the argumentation setting by revising derivations of assertions in light of new information.

We present two multi-agent deontic logics that consistently accommodate various types of normative conflicts. Its language features modal operators for obligation and permission, and for the realization of individual and collective actions. The logic is non-classical since it makes use of a paraconsistent and paracomplete negation connective. Moreover, it is non-monotonic due to its definition within the adaptive logics framework for defeasible reasoning. The logic is equipped with a defeasible proof theory and semantics.

In this article we present the logic MP⊏ that explicates reasoning on the basis of prioritized obligations. Although formal criteria to handle prioritized obligations have been formulated in the literature, little attention has been paid to the actual (non-monotonic) reasoning that makes use of these criteria. The dynamic proof theory of MP⊏ fills this lacuna. This article focuses on premise sets consisting of possibly conflicting prima facie obligations that have a modular order. MP⊏ allows to derive—inter alia—the actual, all-things-considered obligations from such premise sets. It is defined in the format of lexicographic adaptive logics from [34], whence a rich meta-theory is immediately available (e.g. soundness and completeness, idempotence, reflexivity, etc.). In addition, we establish some meta-theoretic results that are specific to the context of prioritized obligations. With the aid of concrete examples, we illustrate properties of MP⊏ which improve on other existing criteria for prioritized obligations.

The article presents a unifying adaptive logic framework for abstract argumentation. It consists of a core system for abstract argumentation and various adaptive logics based on it. These logics represent in an accurate sense all standard extensions defined within Dung’s abstract argumentation system with respect to sceptical and credulous acceptance. The models of our logics correspond exactly to specific extensions of given argument systems. Additionally, the dynamics of adaptive proofs mirror the argumentative reasoning of a rational agent. In particular, the presented logics allow for external dynamics, i.e. they are able to deal with the arrival of new arguments and are therefore apt to model open-ended argumentations by providing provisional conclusions.