Goal-oriented requirements modeling approaches aim to capture the intentions of the stakeholders involved in the development of an information system as goals and tasks. The process of constructing such goal models usually involves discussions between a requirements engineer and a group of stakeholders. Not all the arguments in such discussions can be captured as goals or tasks: e.g., the discussion whether to accept or reject a certain goal and the rationale for acceptance or rejection cannot be captured in goal models. (...) In this paper, we apply techniques from computational argumentation to a goal modeling approach by using a coding analysis in which stakeholders discuss requirements for a Traffic Simulator. We combine a simplified version of a traditional goal model, the Goal-oriented Requirements Language, with ideas from argumentation on schemes for practical reasoning into a new framework. RationalGRL provides a formal semantics and tool support to capture the discussions and outcomes of the argumentation process that leads to a goal model. We also define the RationalGRL development process to create a RationalGRL model. (shrink)

A paramount, yet unresolved issue in personalised medicine is that of automated reasoning with clinical guidelines in multimorbidity settings. This entails enabling machines to use computerised generic clinical guideline recommendations and patient-specific information to yield patient-tailored recommendations where interactions arising due to multimorbidities are resolved. This problem is further complicated by patient management desiderata, in particular the need to account for patient-centric goals as well as preferences of various parties involved. We propose to solve this problem of automated reasoning with (...) interacting guideline recommendations in the context of a given patient by means of computational argumentation. In particular, we advance a structured argumentation formalism ABA+G (short for Assumption-Based Argumentation with Preferences (ABA+) and Goals) for integrating and reasoning with information about recommendations, interactions, patient’s state, preferences and prioritised goals. ABA+G combines assumption-based reasoning with preferences and goal-driven selection among reasoning outcomes. Specifically, we assume defeasible applicability of guideline recommendations with the general goal of patient well-being, resolve interactions (conflicts and otherwise undesirable situations) among recommendations based on the state and preferences of the patient, and employ patient-centered goals to suggest interaction-resolving, goal-importance maximising and preference-adhering recommendations. We use a well-established Transition-based Medical Recommendation model for representing guideline recommendations and identifying interactions thereof, and map the components in question, together with the given patient’s state, prioritised goals, and preferences over actions, to ABA+G for automated reasoning. In this, we follow principles of patient management and establish corresponding theoretical properties as well as illustrate our approach in realistic personalised clinical reasoning scenaria. (shrink)

The principle-based approach is a methodology to classify and analyse argumentation semantics. In this paper we classify seven of the main alternatives for argumentation semantics using a set of new robustness principles. These principles complement Baroni and Giacomin’s original classification and deal with the behaviour of a semantics when the argumentation framework changes due to the addition or removal of an attack between two arguments. We distinguish so-called persistence principles and monotonicity principles, where the former deal with the question of (...) whether a labelling or extension of an argumentation framework under a given semantics persists after a change, and the latter with the question of whether new labellings or extensions are created after a change. We furthermore show in which sense labelling-based and extension-based semantics lead to subtly different principles and results. Our results can be used for choosing a semantics for a particular application, or to guide the search for new argumentation semantics, but they have been used also in the design of algorithms. (shrink)

Online debates typically possess a large number of argumentative comments. Most readers who would like to see which comments are winning arguments often only read a part of the debate. Many platforms that host such debates allow for the comments to be sorted, say from the earliest to latest. How can argumentation theory be used to evaluate the effectiveness of such policies of sorting comments, in terms of the actually winning arguments displayed to a reader who may not have read (...) the whole debate? We devise a pipeline that captures an online debate tree as a bipolar argumentation framework, which is sorted depending on the policy, giving a sequence of induced sub-BAFs representing how and how much of the debate has been read. Each sub-BAF has its own set of winning arguments, which can be quantitatively compared to the set of winning arguments of the whole BAF. We apply this pipeline to evaluate policies on Kialo debates, where it is shown that reading comments from most to least liked, on average, displays more winners than reading comments earliest first. Therefore, in Kialo, reading comments from most to least liked is on average more effective than reading from the earliest to the most recent. (shrink)

In this paper we ask whether approximation for abstract argumentation is useful in practice, and in particular whether reasoning with grounded semantics – which has polynomial runtime – is already an approximation approach sufficient for several practical purposes. While it is clear from theoretical results that reasoning with grounded semantics is different from, for example, skeptical reasoning with preferred semantics, we investigate how significant this difference is in actual argumentation frameworks. As it turns out, in many graphs models, reasoning with (...) grounded semantics actually approximates reasoning with other semantics almost perfectly. An algorithm for grounded reasoning is thus a conceptually simple approximation algorithm that not only does not need a learning phase – like recent approaches – but also approximates well – in practice – several decision problems associated to other semantics. (shrink)

We propose a formal theory built upon an abstract argumentation framework for handling argumentation dynamics. To that end, we analyze the acceptability dynamics of arguments through the proposal of two different kinds of sets of arguments which are somehow responsible for the acceptability/rejection of a given argument. We develop a study of the consequences of breaking the construction of such sets towards the acceptance of an analyzed argument. This brings about the proposal of a novel change operation which allows to (...) determine which arguments should be removed from the framework so that another particular argument becomes accepted. Finally, the proposed model is formalized in the light of the theory of belief revision by characterizing the corresponding operations through constructive definition and an axiomatic characterization, connecting them through the corresponding representation theorem. The theoretical proposal constitutes the fundamentals for a system implementation in many dynamic domains of application. In particular, we show its application for handling the dynamics of legal interpretation. In that sense, this proposal constitutes a fundamental approach and theoretical justification to handle the dynamics of legal arguments through changes of interpretative canons. We show a possible concretisation of our abstract theory for the legal domain by analysing a real legal case from the Argentinean jurisprudence. Such a system would be capable of suggesting alternative critical points in the current state of affairs of a legal case towards pursuing a specific goal for which the case is being investigated. (shrink)

In this work, we question the ability of existing ranking-based semantics to capture persuasion settings, emphasising in particular the phenomena of procatalepsis and of fading. Some widely accepted principles of ranking-based semantics are incompatible with a faithful treatment of these phenomena, which means that no existing ranking-based semantics can capture these two principles together. This motivates us to introduce a new parametrized ranking-based semantics based on the notion of propagation which extends the existing propagation semantics 139–150) by adding an additional (...) parameter allowing us to gradually decrease the impact of arguments when the length of the path between two arguments increases. We show that this parameter gives the possibility of choosing if one wants to satisfy the property Void Precedence or not and to control the scope of the impact of the arguments. We also propose an experiment to show that the new semantics remains stable when this parameter varies and an axiomatic evaluation to compare it with existing ranking-based semantics in the literature. (shrink)

Argumentation has been an important topic in knowledge representation, reasoning and multi-agent systems during the last twenty years. In this paper, we propose a new abstract framework where arguments are associated with a strength, namely a quantitative information which is used to determine whether an attack between arguments succeeds or not. Our Strength-based Argumentation Framework combines ideas of Preference-based and Weighted Argumentation Frameworks in an original way, which permits to define acceptability semantics sensitive to the existence of accruals between arguments. (...) The question of accruals arises in situations where several arguments defending the same position against another argument are unable to individually defeat this argument, but could do it collectively if they combine their strengths. We investigate some of the theoretical and computational properties of our new framework and semantics, and present a reasoning algorithm that is based on a translation of the problem into pseudo-boolean constraint satisfaction. This paper proposes an intuitive framework which allows strength compensations in an argumentation context where attacks may not succeed, completed by an approach which detects accruals throughout the reasoning process without requiring the elicitation of all compensatory combinations of arguments as an input. (shrink)

Structured argumentation formalisms, such as ASPIC +, offer a formal model of defeasible reasoning. Usually such formalisms are highly parametrized and modular in order to provide a unifying framework in which different forms of reasoning can be expressed. This generality comes at the price that, in their most general form, formalisms such as ASPIC + do not satisfy important rationality postulates, such as non-interference. Similarly, links to other forms of knowledge representation, such as reasoning with maximal consistent sets of rules, (...) are insufficiently studied for ASPIC + although such links have been established for other, less complex forms of structured argumentation where defeasible rules are absent. Clearly, for a formal model of defeasible reasoning it is important to understand for which range of parameters the formalism displays a behavior that adheres to common standards of consistency, logical closure and logical relevance and can be adequately described in terms of other well-known forms of knowledge representation. In this paper we answer this question positively for a fragment of ASPIC + without the attack form undercut by showing that it satisfies all standard rationality postulates of structured argumentation under stable and preferred semantics and is adequate for reasoning with maximal consistent sets of defeasible rules. The study is general in that we do not impose any other requirements on the strict rules than to be contrapositable and propositional and in that we also consider priorities among defeasible rules, as long as they are ordered by a total preorder and lifted by weakest link. In this way we generalize previous similar results for other structured argumentation frameworks and so shed further light on the close relations between assumption-based argumentation and ASPIC +. (shrink)

Doug Walton, who died in January 2020, was a prolific author whose work in informal logic and argumentation had a profound influence on Artificial Intelligence, including Artificial Intelligence and Law. He was also very interested in interdisciplinary work, and a frequent and generous collaborator. In this paper seven leading researchers in AI and Law, all past programme chairs of the International Conference on AI and Law who have worked with him, describe his influence on their work.

Cases or examples can be often explained by the interplay of arguments in favour or against their outcomes. This paper addresses the problem of finding explanations for a collection of cases where an explanation is a labelled argumentation graph consistent with the cases, and a case is represented as a statement labelling. The focus is on semi-abstract argumentation graphs specifying attack and subargument relations between arguments, along with particular complete argument labellings taken from probabilistic argumentation where arguments can be excluded. (...) The framework and computational considerations lead to an iterated local iterative deepening depth-first search to collect ‘interesting’ semi-abstract argumentation graphs consistent with a collection of statement labellings. Finally, the framework is illustrated and evaluated with a proof-of-concept implementation. (shrink)

Information technology is so ubiquitous and AI’s progress so inspiring that also legal professionals experience its benefits and have high expectations. At the same time, the powers of AI have been rising so strongly that it is no longer obvious that AI applications (whether in the law or elsewhere) help promoting a good society; in fact they are sometimes harmful. Hence many argue that safeguards are needed for AI to be trustworthy, social, responsible, humane, ethical. In short: AI should be (...) good for us. But how to establish proper safeguards for AI? One strong answer readily available is: consider the problems and solutions studied in AI & Law. AI & Law has worked on the design of social, explainable, responsible AI aligned with human values for decades already, AI & Law addresses the hardest problems across the breadth of AI (in reasoning, knowledge, learning and language), and AI & Law inspires new solutions (argumentation, schemes and norms, rules and cases, interpretation). It is argued that the study of AI as Law supports the development of an AI that is good for us, making AI & Law more relevant than ever. (shrink)

The concept of strong admissibility plays an important role in dialectical proof procedures for grounded semantics allowing, as it does, concise proofs that an argument belongs to the grounded extension without having necessarily to construct this extension in full. One consequence of this property is that strong admissibility ceases to be a unique status semantics. In fact it is straightforward to construct examples for which the number of distinct strongly admissible sets is exponential in the number of arguments. We are (...) interested in characterizing properties of collections of strongly admissible sets in the sense that any system describing the strongly admissible sets of an argument framework must satisfy particular criteria. In terms of previous studies, our concern is the signature and with conditions ensuring realizability. The principal result is to demonstrate that a system of sets describes the strongly admissible sets of some framework if and only if that system has the property of being decomposable. (shrink)

Multimorbidity, the presence of multiple health conditions that must be addressed, is a particularly difficult situation in patient management raising issues such as the use of multiple drugs and drug-disease interactions. Clinical Guidelines are evidence-based statements which provide recommendations for specific health conditions but are unfit for the management of multiple co-occurring health situations. To leverage these evidence-based documents, it becomes necessary to combine them. In this paper, using a case example, we explore the use of argumentation schemes to reason (...) and combine evidence-based recommendations from clinical guidelines, expected effects, conflicts stemming from said recommendations, and preferences regarding treatment goals. We compare the results of reasoning using the schemes for practical reasoning and argument from negative consequences in the Carneades Argumentation System with those of ASPIC-G, an extension of the artificial intelligence system ASPIC+. (shrink)

Presenting the first comprehensive, in-depth study of hyperintensionality, this book equips readers with the basic tools needed to appreciate some of current and future debates in the philosophy of language, semantics, and metaphysics. After introducing and explaining the major approaches to hyperintensionality found in the literature, the book tackles its systematic connections to normativity and offers some contributions to the current debates. The book offers undergraduate and graduate students an essential introduction to the topic, while also helping professionals in related (...) fields get up to speed on open research-level problems. (shrink)

In this paper we introduce hypersequent-based frameworks for the modelling of defeasible reasoning by means of logic-based argumentation and the induced entailment relations. These structures are an extension of sequent-based argumentation frameworks, in which arguments and the attack relations among them are expressed not only by Gentzen-style sequents, but by more general expressions, called hypersequents. This generalization allows us to overcome some of the known weaknesses of logical argumentation frameworks and to prove several desirable properties of the entailments that are (...) induced by the extended frameworks. It also allows us to incorporate as the deductive base of our formalism some well-known logics, which lack cut-free sequent calculi, and so are not adequate for standard sequent-based argumentation. We show that hypersequent-based argumentation yields robust defeasible variants of these logics, with many desirable properties. (shrink)

Abductive problems and their solutions are presented by means of justification logic. We introduce additional meta-constructions in order to generate and compare different solutions to the same abductive problem. Our approach has three advantages: (i) it makes structurally explicit the solution to an abductive problem (as it has a syntactic nature); (ii) it gives a precise meaning to the notion of evidence; (iii) it provides clear definitions and procedures for the comparison of solutions that can be adapted to different needs.

Argument evaluation, one of the central problems in argumentation theory, consists in studying what makes an argument a good one. This paper proposes a formal approach to argument evaluation from the perspective of justification logic. We adopt a multi-agent setting, accepting the intuitive idea that arguments are always evaluated by someone. Two general restrictions are imposed on our analysis: non-deductive arguments are left out and the goal of argument evaluation is fixed: supporting a given proposition. Methodologically, our approach uses several (...) existing tools borrowed from justification logic, awareness logic, doxastic logic and logics for belief dependence. We start by introducing a basic logic for argument evaluation, where a list of argumentative and doxastic notions can be expressed. Later on, we discuss how to capture the mentioned form of argument evaluation by defining a preference operator in the object language. The intuitive picture behind this definition is that, when assessing a couple of arguments, the agent puts them to a test consisting of several criteria. As a result of this process, a preference relation among the evaluated arguments is established by the agent. After showing that this operator suffers a special form of logical omniscience, called preferential omniscience, we discuss how to define an explicit version of it, more suitable to deal with non-ideal agents. The present work exploits the formal notion of awareness in order to model several informal phenomena: awareness of sentences, availability of arguments and communication between agents and external sources. We discuss several extensions of the basic logic and offer completeness and decidability results for all of them. (shrink)

Recent studies of scientific interaction based on agent-based models suggest that a crucial factor conducive to efficient inquiry is what Zollman has dubbed ‘transient diversity’. It signifies a process in which a community engages in parallel exploration of rivaling theories lasting sufficiently long for the community to identify the best theory and to converge on it. But what exactly generates transient diversity? And is transient diversity a decisive factor when it comes to the efficiency of inquiry? In this paper we (...) examine the impact of different conditions on the efficiency of inquiry, as well as the relation between diversity and efficiency. This includes certain diversity-generating mechanisms previously proposed in the literature, as well as some factors that have so far been neglected. This study is obtained via an argumentation-based ABM. Our results suggest that cautious decision-making does not always have a significant impact on the efficiency of inquiry while different evaluations underlying theory-choice and different social networks do. Moreover, we find a correlation between diversity and a successful performance of agents only under specific conditions, which indicates that transient diversity is sometimes not the primary factor responsible for efficiency. Altogether, when comparing our results to those obtained by structurally different ABMs based on Zollman’s work, the impact of specific factors on efficiency of inquiry, as well as the role of transient diversity in achieving efficiency, appear to be highly dependent on the underlying model. (shrink)

The Logocratic Method, and the Logocratic theory that underwrites it, provide a philosophical explanation of three purposes or goals that arguers have for their arguments: to make arguments that are internally strong, or that are dialectically strong, or that are rhetorically strong. This article presents the basic terms and methods of Logocratic analysis and then uses a case study to illustrate the Logocratic explanation of arguments. Highlights of this explanation are: the use of a virtue framework to explicate the three (...) strengths and weaknesses of arguments that are of greatest interest to arguers in many contexts, the Logocratic explication of the structure of abduction generally and of legal abduction specifically, the concept of a system of arguments, and the concept of the dynamic interactive virtue of arguments—a property of systems of arguments in which the system of arguments as a whole is as virtuous as are the component arguments that comprise the system. This is especially important since, according to Logocratic theory, some arguments, such as abduction and analogical argument, are themselves comprised of different logical forms. (shrink)

Abstract. The notion of similarity has been studied in many areas of Computer Science; in a general sense, this concept is defined to provide a measure of the semantic equivalence between two pieces of knowledge, expressing how “close” their meaning can be regarded. In this work, we study similarity as a tool useful to improve the representation of arguments, the interpretation of the relations between arguments, and the semantic evaluation associated with the arguments in the argumentative process. In this direction, (...) we present a novel mechanism to determine the similarity between two arguments based on descriptors representing particular aspects associated with these arguments. This mechanism involves a comparison process influenced by the context in which the process develops, where this context provides the relevant aspects that need to be analyzed in the application domain. Then, we use this similarity measure as a quantity to compute the result of attacks and supports in the argumentation process. These valuations, applied to a Bipolar Argumentation Frameworks, allowed us to refine the argument relations, providing the tools to establish a family of new argumentation semantics that considers the similarity between arguments as a crucial part for the argumentation process. (shrink)

While the philosophical literature has extensively studied how decisions relate to arguments, reasons and justifications, decision theory almost entirely ignores the latter notions. In this article, we elaborate a formal framework to introduce in decision theory the stance that decision-makers take towards arguments and counter-arguments. We start from a decision situation, where an individual requests decision support. We formally define, as a commendable basis for decision-aid, this individual’s deliberated judgment, a notion inspired by Rawls’ contributions to the philosophical literature, and (...) embodying the requirement that the decision-maker should carefully examine arguments and counter-arguments. We explain how models of deliberated judgment can be validated empirically. We then identify conditions upon which the existence of a valid model can be taken for granted, and analyze how these conditions can be relaxed. We then explore the significance of our framework for the practice of decision analysis. Our framework opens avenues for future research involving both philosophy and decision theory, as well as empirical implementations. (shrink)

The article develops and justifies, on the basis of the epistemological argumentation theory, two central pieces of the theory of evaluative argumentation interpretation: 1. criteria for recognizing argument types and 2. rules for adding reasons to create ideal arguments. Ad 1: The criteria for identifying argument types are a selection of essential elements from the definitions of the respective argument types. Ad 2: After presenting the general principles for adding reasons (benevolence, authenticity, immanence, optimization), heuristics are proposed for finding missing (...) reasons, for deductive arguments, e.g., semantic tableaux are suggested. (shrink)

The Logocratic Method, and the Logocratic theory that underwrites it, provide a philosophical explanation of three purposes or goals that arguers have for their arguments: to make arguments that are internally strong, or that are dialectically strong, or that are rhetorically strong. This article presents the basic terms and methods of Logocratic analysis and then uses a case study to illustrate the Logocratic explanation of arguments. Highlights of this explanation are: the use of a virtue framework to explicate the three (...) strengths and weaknesses of arguments that are of greatest interest to arguers in many contexts, the Logocratic explication of the structure of abduction generally and of legal abduction specifically, the concept of a system of arguments, and the concept of the dynamic interactive virtue of arguments—a property of systems of arguments in which the system of arguments as a whole is as virtuous as are the component arguments that comprise the system. This is especially important since, according to Logocratic theory, some arguments, such as abduction and analogical argument, are themselves comprised of different logical forms. (shrink)

In the court of law, a person can be punished for attempting to commit a crime. An open issue in the study of Artificial Intelligence and Law is whether the law of attempts could be formally modelled. There are distinct legal rules for determining attempted crime whereas the last-act rule (also called proximity rule) represents the strictest approach. In this paper, we provide a formal model of the last-act rule using structured argumentation.

This paper presents a way in which formal logic can be understood and reformulated in terms of argumentation that can help us unify formal and informal reasoning. Classical deductive reasoning will be expressed entirely in terms of notions and concepts from argumentation so that formal logical entailment is equivalently captured via the arguments that win between those supporting concluding formulae and arguments supporting contradictory formulae. This allows us to go beyond Classical Logic and smoothly connect it with human reasoning, thus (...) providing a uniform argumentation-based view of both informal and formal logic. (shrink)

Scientific research in the formal sciences comes in multiple degrees of formality: fully formal work; rigorous proofs that practitioners know to be formalizable in principle; and informal work like rough proof sketches and considerations about the advantages and disadvantages of various formal systems. This informal work includes informal and semi-formal debates between formal scientists, e.g. about the acceptability of foundational principles and proposed axiomatizations. In this paper, we propose to use the methodology of structured argumentation theory to produce a formal (...) model of such informal and semi-formal debates in the formal sciences. For this purpose, we propose ASPIC-END, an adaptation of the structured argumentation framework ASPIC+ which can incorporate natural deduction style arguments and explanations. We illustrate the applicability of the framework to debates in the formal sciences by presenting a simple model of some arguments about proposed solutions to the Liar paradox, and by discussing a more extensive—but still preliminary—model of parts of the debate that mathematicians had about the Axiom of Choice in the early twentieth century. (shrink)

Bex analyzes the case with an informal version of his hybrid theory, which combines scenario construction and argumentation. Arguments based on evidence can be used to reason about alternative scenarios. Bex claims that his hybrid theory provides the best of both worlds by combining cognitively feasible story‐based reasoning with more detailed rational argumentation. However, like the argument‐based approach, the hybrid theory does not provide a systematic account of uncertainty.

Throughout this paper, we are trying to show how and why our Mathematical frame-work seems inappropriate to solve problems in Theory of Computation. More exactly, the concept of turning back in time in paradoxes causes inconsistency in modeling of the concept of Time in some semantic situations. As we see in the first chapter, by introducing a version of “Unexpected Hanging Paradox”,first we attempt to open a new explanation for some paradoxes. In the second step, by applying this paradox, it (...) is demonstrated that any formalized system for the Theory of Computation based on Classical Logic and Turing Model of Computation leads us to a contradiction. We conclude that our mathematical frame work is inappropriate for Theory of Computation. Furthermore, the result provides us a reason that many problems in Complexity Theory resist to be solved.(This work is completed in 2017 -5- 2, it is in vixra in 2017-5-14, presented in Unilog 2018, Vichy). (shrink)

This paper examines lessons obtained by means of simulations in the form of agent-based models about the norms that are to guide disagreeing scientists. I focus on two types of epistemic and methodological norms: norms that guide one’s attitude towards one’s own theory, and norms that guide one’s attitude towards the opponent’s theory. Concerning I look into ABMs that have been designed to examine the context of peer disagreement. Here I challenge the conclusion that the given ABMs provide a support (...) for the so-called Steadfast Norm, according to which one is epistemically justified in remaining steadfast in their beliefs in face of disagreeing peers. I argue that the proposed models at best provide evidence for a weaker norm, which concerns methodological steadfastness. Concerning I look into ABMs aimed at examining epistemic effects of scientific interaction. Here I argue that the models provide diverging suggestions and that the link between each ABM and the type of represented inquiry is still missing. Moreover, I examine alternative strategies of arguing in favor of the benefits of scientific interaction, relevant for contemporary discussions on scientific pluralism. (shrink)