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DAQAP: Defeasible Argumentation Query Answering Platform
Abstract
In this paper we present the DAQAP, a Web platform for Defeasible Argumentation Query Answering, which offers a visual interface that facilitates the analysis of the argumentative process defined in the Defeasible Logic Programming (DeLP) formalism. The tool presents graphs that show the interaction of the arguments generated from a DeLP program; this is done in two different ways: the first focuses on the structures obtained from the DeLP program, while the second presents the defeat relationships from the point of view of abstract argumentation frameworks, with the possibility of calculating the extensions using Dung’s semantics. Using all this data, the platform provides support for answering queries regarding the states of literals of the input program.
... • A use case for the application of a structured probabilistic argumentation model (DeLP3E) [18] based on publicly available cybersecurity datasets. • Design of the P-DAQAP framework, an extension of DAQAP [19], to work with DeLP3E, and the proposal of different classes of queries in the context of applications related to CTA. • A preliminary empirical evaluation of an approximation algorithm for probabilistic query answering in P-DAQAP, showing the potential for the system to scale to nontrivial problem sizes, arriving at solutions efficiently and effectively. ...
... There are several formalisms that are based on this idea, such as ABA [21], ASPIC+ [22], defeasible logic programming (DeLP) [23], and deductive argumentation [24], which consider the structure of the arguments that model a discussion. The DAQAP platform [19] on which the presented system is based uses DeLP as its central formalism. We now briefly present the necessary background, starting with DeLP and its probabilistic extension. ...
... In an early version of the platform called DAQAP [19], we developed a web-based client-server platform that offers an interface to visualize the interaction of the arguments generated from an input DeLP program via dialectical trees and graphs, as well as the abstract defeat relationships in a Dung-like graph environment. In this section, we present the extension that incorporates probabilistic reasoning based on DeLP3E knowledge bases, first briefly discussing the platform's architecture and workflow, and then moving on to presenting a set of features that could eventually support human-in-the-loop reasoning and XAI functionalities. ...
Decision support tools are key components of intelligent sociotechnical systems, and their successful implementation faces a variety of challenges, including the multiplicity of information sources, heterogeneous format, and constant changes. Handling such challenges requires the ability to analyze and process inconsistent and incomplete information with varying degrees of associated uncertainty. Moreover, some domains require the system’s outputs to be explainable and interpretable; an example of this is cyberthreat analysis (CTA) in cybersecurity domains. In this paper, we first present the P-DAQAP system, an extension of a recently developed query-answering platform based on defeasible logic programming (DeLP) that incorporates a probabilistic model and focuses on delivering these capabilities. After discussing the details of its design and implementation, and describing how it can be applied in a CTA use case, we report on the results of an empirical evaluation designed to explore the effectiveness and efficiency of a possible world sampling-based approximate query answering approach that addresses the intractability of exact computations.
... In the next section, we present an example of how DeLP3E can be used in practice, leveraging our recently-introduced graphical tool [6]. ...
Capturing the uncertain aspects in cyber threat analyses is an important part of a wide range of efforts, including diagnostics, threat evaluation, and preventing attacks. However, there has been insufficient research and development of modeling approaches that are able to correctly capture and handle such uncertainty. In this work, we present an application example of the DeLP3E framework-a formalism that extends structured argumentation based on logic programming-in the domain of cyber threat analysis; in particular, near real-time analyses such as incident response in enterprise networks. The DeLP3E framework provides a unique combination of dialectical reasoning, rule-based inference , and probabilistic modeling to not only offer suggested responses to given situations, but also to explain to the analyst why the system reaches its conclusions.
... Argument mapping provides intuitive and effective support for critical thinking (Reed and Rowe, 2004;van Gelder, 2007), and shows advantages particularly in enriching and understanding of a problem over for example text representations (Carneiro et al., 2021), but does not offer support for reasoning. Argument mapping and formal argumentation can be combined to visualise and analyse arguments or conclusions (Leiva et al., 2019;Reed et al., 2017). In this work, we also combine these approaches to enable analysts to directly interact and benefit from a computational model of argumentation in the construction and evaluation of hypotheses. ...
In this paper we illustrate how novel AI methods can improve the performance of intelligence analysts. These analysts aim to make sense of — often conflicting or incomplete — information, weighing up competing hypotheses which serve to explain an observed situation. Analysts have access to numerous visual analytic tools which support the temporal and/or conceptual structuring of information and collection, and support the evaluation of alternative hypotheses. We believe however that there are currently no tools or methods which allow analysts to combine the recording and interpretation of information, and that there is little understanding about how software tools can facilitate the hypothesis formation process. Following the identification of these requirements, we developed the CISpaces (Collaborative Intelligence Spaces) decision support tool in collaboration with professional intelligence analysts. CISpaces combines multiple AI-based methods including argumentation theory, crowdsourced Bayesian analysis, and provenance recording. We show that CISpaces is able to provide support to analysts by facilitating the interpretation of different types of evidence through argumentation-based reasoning, provenance analysis and crowdsourcing. We undertook an experimental analysis with intelligence analysts which highlights three key points. (1) The novel, principled AI methods implemented in CISpaces advance performance in intelligence analysis. (2) While designed as a research prototype (at TRL 3), analysts benchmarked it against their existing software tools, and we provide results suggesting intention to adopt CISpaces in analysts’ daily activities. (3) Finally, the evaluation highlights some drawbacks in CISpaces. However, these are not due to the technologies underpinning the tool, but rather its lack of integration with existing organisational standards regarding input and output formats. Our evaluation with intelligence analysts therefore demonstrates the potential impact that an integrated tool building on state-of-the-art AI techniques can have on the process of understanding complex situations, and on how such a tool can help focus human effort on identifying more credible interpretations of evidence.
... Future work presents different possibilities, such as the development of an implementation of S-BAFsby using the existing DeLP [35,36,52] system as a basis. 2 The resulting implementation will be applied to different domains that require modeling decision support systems associated with context restrictions that model the users' preferences. Furthermore, we are working to generalize the function of similarity in such a way as to contemplate more broad domains. ...
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.
... In the literature, it is possible to find several preference-based argumentation frameworks [73][74][75]; however, the use of multiple criteria has not been addressed in these frameworks. One future goal is to define an abstract argumentation framework which includes the combined-preference expressions in its formalism and allows to handle several preference relations. ...
As a practical mechanism for formalizing commonsense reasoning, argumentation has shown its potential for applications in diverse areas, many related to decision-making in knowledge-based systems. Following this line, and for helping users in making a better and informed decision, different recommender systems proposals have been developed in the argumentation literature. We will use recommender systems as a good example where to exercise our proposal. In particular, the role of preference criterion in argumentation-based recommender systems which is used to compare competing arguments is central to the user’s query answering process where if the criterion does not adjust to the represented domain, the system could fail by being undecided too often. Therefore, having tools that allow to select and change the argument comparison mechanism has to be used become a central issue. Argumentation-based recommender systems that offer these tools provide an interesting ability that can be used for improving the reasoning capabilities in this type of systems. This work introduces an approach to handle multiple argument preference criteria in argumentation-based recommender systems and general knowledge-based decision support systems. More precisely, the proposal allows changing the information that a criterion can use in the argument comparison process and specify how several criteria can be simultaneously used in such process as well; to achieve that goal, a set of operators to combine several criteria is presented. The knowledge representation and reasoning is performed in Defeasible Logic Programming, a defeasible argumentation formalism based on logic programming.
The representation of argumentation is based on various forms of structured and non-structured presentation of arguments. Among them, graphic ones deserve special attention, since they are more expressive and, in addition to practical application, can be used for methodological purposes when teaching argumentation. With the development of information and communication technologies, since the mid-noughties of the XXI century, software has been developed designed to represent argumentation and evidence-based reasoning. Since the middle of the XX century, within the framework of research conducted by argumentation theorists, theoretical approaches to the representation of argumentation have been developed, which form the basis of the representation of argumentation by means of software. The graphical capabilities of modern hardware and software are used for visual representation of argumentation. This study examines the possibilities of existing software for visualizing argumentation. The connection of visualization with the theoretical foundations of the representation of argumentation is analyzed, its features are revealed.
A rule based knowledge system consists of three main components: a set of rules, facts to be fed to the reasoning corresponding to the data of a case, and an inference engine. In general, facts are stored in (relational) databases that represent knowledge in a first-order based formalism. However, legal knowledge uses defeasible deontic logic for knowledge representation due to its particular features that cannot be supported by first-order logic. In this work, we present a unified framework that supports efficient legal reasoning. In the framework, a novel inference engine is proposed in which the Semantic Rule Index can identify candidate rules with their corresponding semantic rules if any, and an inference controller is able to guide the executions of queries and reasoning. It can eliminate rules that cannot be fired to avoid unnecessary computations in early stages. The experiments demonstrated the effectiveness and efficiency of the proposed framework.
Critical thinking about international politics often involves reasoning about the beliefs, goals, appraisals, actions, and plans of actors such as countries, governments, politicians, etc. We analyzed arguments in interpretive reports about international politics, in order to develop a prototype argument diagramming tool for this domain, AVIZE (Argument Visualization and Evaluation). The purpose of AVIZE is to aid users in the construction and self-evaluation of real-world arguments in the domain of international politics. AVIZE provides a set of argument schemes as cognitive building blocks for constructing argument diagrams. Most of the schemes are related to concepts from the field of automated plan recognition in artificial intelligence. While some currently available argument diagramming tools provide schemes, they are not tailored to the domain of international politics. This paper describes the argument schemes for this domain and the design of the argument diagramming tool.
This paper presents OpMAP: A tool for visualizing large scale, multi-dimensional opinion spaces as geographic maps. OpMAP represents opinions as labelings on a structured deductive argumentation framework. It uses probabilistic degrees of justification and Bayesian coherence measures to calculate how strongly any two opinions cohere with each other. The opinion sample is, accordingly, represented as a weighted graph, a so-called opinion graph, with opinion vectors serving as nodes and coherence values as edge weights. OpMAP partitions the nodes of the opinion graph by using clustering methods. Finally, the graph is visualized as a geographic map using a method based on a particular (e.g., force-directed) layout.
This is an open access paper, the full text is freely available from the publisher at https://dx.doi.org/10.3233/AAC-181004
This paper introduces OVA+, an on-line interface for the analysis of arguments. It is the result of an attempt to provide a tool relying on the Argument Interchange Format theory and Inference Anchoring Theory schemes.
In abstract argumentation, each argument is regarded as atomic. There is no internal structure to an argument. Also, there is no specification of what is an argument or an attack. They are assumed to be given. This abstract perspective provides many advantages for studying the nature of argumentation, but it does not cover all our needs for understanding argumentation or for building tools for supporting or undertaking argumentation. If we want a more detailed formalisation of arguments than is available with abstract argumentation, we can turn to structured argumentation, which is the topic of this special issue of Argument and Computation. In structured argumentation, we assume a formal language for representing knowledge, and specifying how arguments and counterarguments can be constructed from that knowledge. An argument is then said to be structured in the sense that normally the premises and claim of the argument are made explicit, and the relationship between the premises and claim is formally defined (for instance using logical entailment). In this introduction, we provide a brief overview of the approaches covered in this special issue on structured argumentation.
Reasoning and argumentation are at the very heart of philosophy. A series of classic arguments is a large part of our subject matter, and argumentation is our primary means of making progress. And one of the main benefits of studying philosophy is that it is supposed to enhance reasoning abilities. As a profession, we have standard practices for handling reasoning and argumentation. One feature of these practices is so familiar and pervasive that it is almost invisible: the medium of philosophical argumentation is prose. We spend a great deal of time articulating arguments in written prose, and identifying arguments in the writings of others. The dominance of prose goes beyond writing; even when discussing arguments or jousting philosophically, we are using prose, albeit in its spoken form. Sometimes we do use other methods. Occasionally, for example, we shift from standard natural-language prose into the medium of formal logic. And even when using prose, we add special terminology, strategies and conventions. Yet these idiosyncrasies don't alter the fact that, overwhelmingly, philosophers handle arguments in prose. Interestingly, in this regard little has changed in thousands of years. That is why we can expect our undergraduate students to engage as productively with the writings of Plato and Aristotle as they can with the latest textbooks and journal articles. We do have new technological supports such as word processors and email. What we do with this new technology, however, is very much the same as would have been done 200 or 2,000 years ago. Descartes hand-wrote letters to Queen Christina; we now send Word documents as email attachments. But these are superficial differences; in both cases, the philosophical work is largely a matter of expressing arguments in lengthy concatenations of words and sentences. Is this constancy simply due to the fact that philosophical argument is somehow essentially prose-based? Not at all. As already noted, philosophers find that certain arguments are best handled by shifting to symbolic logic, though formal techniques are only useful in a narrow range of cases. However there is now emerging another alternative to prose, one which is naturally suited to the vast range of argumentation which is intrinsically informal. That alternative is computer-supported argument mapping (Kirschner, Buckingham Shum, & Carr, forthcoming).
This paper introduces AIFdb, a database solution for the Argument Web. AIFdb offers an array of web service interfaces allowing a wide range of software to interact with the same argument data.
Most formalisms for representing common-sense knowledge allow incomplete and potentially inconsistent information. When strong negation is also allowed, contradictory con-clusions can arise. A criterion for deciding between them is needed. The aim of this paper is to investigate an inherent and autonomous comparison criterion, based on specificity as defined in [POO 85, SIM 92]. In contrast to other approaches, we consider not only defeasible, but also strict knowledge. Our criterion is context-sensitive, i. e., preference among defeasible rules is determined dynamically during the dialectical analysis. We show how specificity can be defined in terms of two different approaches: activation sets and derivation trees. This allows us to get a syntactic criterion that can be implemented in a computationally attractive way. The resulting definitions may be applied in general rule-based formalisms. We present theorems linking both characterizations. Finally we discuss other frameworks for defeasible reasoning in which preference handling is considered explicitly.
This paper presents an overview on the state of the art of semantics for abstract
argumentation, covering both some of the most influential literature proposals
and some general issues concerning semantics definition and evaluation. As to
the former point, the paper reviews Dung's original notions of
complete, grounded, preferred, and stable semantics, as well as subsequently
proposed notions like semi-stable, ideal, stage, and CF2 semantics, considering
both the extension-based and the labelling-based approaches with respect to
their definitions. As to the latter point, the paper presents an extensive set
of general properties for semantics evaluation and analyzes the notions of
argument justification and skepticism. The final part of the paper is focused on
the discussion of some relationships between semantics properties and
domain-specific requirements.
Argumentation theory involves the analysis of naturally occurring argument, and one key tool employed to this end both in the academic community and in teaching critical thinking skills to undergraduates is argument diagramming. By identifying the structure of an argument in terms of its constituents and the relationships between them, it becomes easier to critically evaluate each part of an argument in turn. The task of analysis and diagramming, however, is labor intensive and often idiosyncratic, which can make academic exchange difficult. The Araucaria system provides an interface which supports the diagramming process, and then saves the result using AML, an open standard, designed in XML, for describing argument structure. Araucaria aims to be of use not only in pedagogical situations, but also in support of research activity. As a result, it has been designed from the outset to handle more advanced argumentation theoretic concepts such as schemes, which capture stereotypical patterns of reasoning. The software is also designed to be compatible with a number of applications under development, including dialogic interaction and online corpus provision. Together, these features, combined with its platform independence and ease of use, have the potential to make Araucaria a valuable resource for the academic community.
This document describes a strawman specification for an Ar- gument Interchange Format (AIF) that might be used for data exchange between Argumentation tools or communication in Multi-Agent Sys- tems (MAS). The document started life as a skeleton for contributions from participants in the Technical Forum Group meeting in Budapest in September 2005, receiving also input from third parties. The results were subsequentely improved and added to by online discussion to form a more substantial. In its current form, this document is intended to be a strawman model which serves as a point of discussion for the community rather than an attempt at a definitive, all encompassing model. The hope is that it could provide a useful input to ArgMAS discussion in paricu- lar on the utility of common Argumentation Interchange Formats, what form they might take and a potential research / development agenda to help realise them.
This paper provides an assessment of the most recent empirical research into the effectiveness of argument visualization tools. In particular, the methodological quality of the reported experiments and the conclusions drawn from them are critically examined. Their validity is determined and the methodological differences between them are clarified. The discrepancies in intended effects of use especially are investigated. Subsequently, methodological recommendations for future experiments are given.
: We describe "Belvedere," a system to support students engaged in critical discussion of science issues. The design is intended to address cognitive and metacognitive limitations of unpracticed beginners while supporting their practice of this complex skill. Both prior psychological research and formativeevaluation studies with users shaped the interface design. We discuss our design rationale, describe our formative evaluation studies and provide examples of student sessions, and discuss ongoing work with the argumentation advisor. Introduction An early and persistent interest in designing software systems to support argumentation resulted in interesting work with hypertext systems and with graphical interfaces for argument construction (Conklin & Begeman, 1987; Fischer, McCall, &Morch, 1989; Smolensky, Fox, King, & Lewis, 1987; Streitz, Hannemann, & Thuring, 1989). For the most part, these systems are designed to provide either a medium for a generic competent reasoner, or s...
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.
Argumentation represents a way of reasoning over a knowledge base containing possibly incomplete and/or inconsistent information, to obtain useful conclusions. As a reasoning mechanism, the way an argumentation reasoning engine reaches these conclusions resembles the cognitive process that humans follow to analyse their beliefs; thus, unlike other computationally reasoning systems, argumentation offers an intellectually friendly alternative to other defeasible reasoning systems. Logic Programming is a computational paradigm that has produced computationally attractive systems with remarkable success in many applications. Merging ideas from both areas, Defeasible Logic Programming offers a computational reasoning system that uses an argumentation engine to obtain answers from a knowledge base represented using a logic programming language extended with defeasible rules. This combination of ideas brings about a computationally effective system together with a human-like reasoning model facilitating its use in applications.
The present paper discusses experimental argument assistance tools. In contrast with automated reasoning tools, the objective is not to replace reasoning, but to guide the user's production of arguments. Two systems are presented, Argue! and ArguMed based on DefLog. The focus is on defeasible argumentation with an eye on the law. Argument assistants for defeasible argumentation naturally correspond to a view of the application of law as dialectical theory construction. The experiments provide insights into the design of argument assistants, and show the pros and cons of different ways of representing argumentative data. The development of the argumentation theories underlying the systems has culminated in the logical system DefLog that formalizes the interpretation of prima facie justified assumptions. DefLog introduces an innovative use of conditionals expressing support and attack. This allows the expression of warrants for support and attack, making it a transparent and flexible system of defeasible argumentation.
The purpose of this paper is to study the fundamental mechanism, humans use in argumentation, and to explore ways to implement this mechanism on computers.We do so by first developing a theory for argumentation whose central notion is the acceptability of arguments. Then we argue for the “correctness” or “appropriateness” of our theory with two strong arguments. The first one shows that most of the major approaches to nonmonotonic reasoning in AI and logic programming are special forms of our theory of argumentation. The second argument illustrates how our theory can be used to investigate the logical structure of many practical problems. This argument is based on a result showing that our theory captures naturally the solutions of the theory of n-person games and of the well-known stable marriage problem.By showing that argumentation can be viewed as a special form of logic programming with negation as failure, we introduce a general logic-programming-based method for generating meta-interpreters for argumentation systems, a method very much similar to the compiler-compiler idea in conventional programming.
This paper describes Convince Me, a tool for generating and analyzing arguments. Results indicate that the system makes people better reasoners while they employ it, and yields transfer to situations unsupported by the software.
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