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Johannes Peter Wallner

Johannes Peter Wallner

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69
Publications
2,594
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979
Citations
Introduction
My profile on ResearchGate is not maintained. Regarding requests for full texts: in most cases a version of that paper is available. See, e.g., my personal webpage: http://jpwallner.name, which I update somewhat regularly (otherwise send me an email). I do not usually respond to individual requests on ResearchGate within a short time (I only check from time to time). best, Johannes

Publications

Publications (69)
Conference Paper
Abstract dialectical frameworks (ADFs) have recently been proposed as a versatile generalization of Dung's abstract argumentation frameworks (AFs). In this paper, we present a comprehensive analysis of the computational complexity of ADFs. Our results show that while ADFs are one level up in the polynomial hierarchy compared to AFs, there is a usef...
Conference Paper
We present various new concepts and results related to abstract dialectical frameworks (ADFs), a powerful generalization of Dung's argumentation frameworks (AFs). In particular, we show how the existing definitions of stable and preferred semantics which are restricted to the subcase of so-called bipolar ADFs can be improved and generalized to arbi...
Conference Paper
In the area of propositional satisfiability (SAT), tremendous progress has been made in the last decade. Today’s SAT technology covers not only the standard SAT problem, but also extensions thereof, such as computing a backbone (the literals which are true in all satisfying assignments) or minimal corrections sets (minimal subsets of clauses which...
Article
Abstract argumentation frameworks (AFs) provide the basis for various reasoning problems in the area of Artificial Intelligence. Efficient evaluation of AFs has thus been identified as an important research challenge. So far, implemented systems for evaluating AFs have either followed a straight-forward reduction-based approach or been limited to c...
Article
Full-text available
Dung's famous abstract argumentation frameworks represent the core formalism for many problems and applications in the field of argumentation which significantly evolved within the last decade. Recent work in the field has thus focused on implementations for these frameworks, whereby one of the main approaches is to use Answer-Set Programming (ASP)...
Conference Paper
We provide complexity results and algorithms for reasoning in the central structured argumentation formalism of ASPIC+. Considering ASPIC+ accommodated with preferences under the last-link principle, the results are made possible by rephrasing several argumentation semantics---admissible, complete, stable, preferred and grounded---in terms of defea...
Conference Paper
Approaches to computational argumentation provide foundational ways to reason argumentatively within Artificial Intelligence (AI). The underlying formal approaches can oftentimes be classified into structured argumentation and abstract argumentation. The former prescribe rigorous workflows, starting from knowledge bases to finding arguments in favo...
Conference Paper
Reasoning with defeasible and conflicting knowledge in an argumentative form is a key research field in computational argumentation. Reasoning under various forms of uncertainty is both a key feature and a challenging barrier for automated argumentative reasoning. It was shown that argumentative reasoning using probabilities faces in general high c...
Conference Paper
This overview accompanies the author's Early Career Track presentation. We survey recent research and research agenda of the author, focusing on contributions in the area of computational argumentation. Contributions span from foundations of static and dynamic forms of argumentative reasoning and approaches to support explainability, e.g., analysis...
Conference Paper
Most existing computational tools for assumption-based argumentation (ABA) focus on so-called flat frameworks, disregarding the more general case. In this paper, we study an instantiation-based approach for reasoning in possibly non-flat ABA. We make use of a semantics-preserving translation between ABA and bipolar argumentation frameworks (BAFs)....
Preprint
Full-text available
Reasoning with defeasible and conflicting knowledge in an argumentative form is a key research field in computational argumentation. Reasoning under various forms of uncertainty is both a key feature and a challenging barrier for automated argumentative reasoning. It was shown that argumentative reasoning using probabilities faces in general high c...
Conference Paper
We present a general framework to rank assumption in assumption based argumentation frameworks (ABA frameworks), relying on their relationship to other assumptions and the syntactical structure of the ABA framework. We propose a new family of semantics for ABA frameworks that is using reductions to the abstract argumentation setting and leveraging...
Chapter
Full-text available
We address complex reasoning tasks in assumption-based argumentation (ABA) by developing dynamic programming algorithms based on tree-decompositions. As one of the prominent approaches in computational argumentation, our focus is on NP-hard reasoning in ABA. We utilize tree-width, a structural measure describing closeness to trees, for an approach...
Conference Paper
Reasoning under incomplete information is an important research direction in AI argumentation. Most computational advances in this direction have so-far focused on abstract argumentation frameworks. Development of computational approaches to reasoning under incomplete information in structured formalisms remains to-date to a large extent a challeng...
Conference Paper
A key ingredient of computational argumentation in AI is the generation of arguments in favor of or against claims under scrutiny. In this paper we look at the complexity of argument construction and reasoning in the prominent structured formalism of assumption-based argumentation (ABA). We point out that reasoning in ABA by means of constructing a...
Chapter
Full-text available
Computational argumentation is primed to strengthen the current hot research field of Explainable Artificial Intelligence (XAI), e.g., by dialectical approaches. In this paper, we extend and discuss a recently proposed approach of so-called strong acceptance on abstract argumentation that aims to support explaining argumentative acceptance. Our goa...
Chapter
Full-text available
Assumption-based argumentation (ABA) is one of the most-studied formalisms for structured argumentation. While ABA is a general formalism that can be instantiated with various different logics, most attention from the computational perspective has been focused on the logic programming (LP) instantiation of ABA. Going beyond the LP-instantiation, we...
Chapter
Abstract dialectical frameworks (ADFs) are a well-studied generalisation of the prominent argumentation frameworks due to Phan Minh Dung. In this paper we propose to use reduced ordered binary decision diagrams (roBDDs) as a suitable representation of the acceptance conditions of arguments within ADFs. We first show that computational complexity of...
Conference Paper
Rephrasing argumentation semantics in terms of subsets of defeasible elements allows for gaining new insights for reasoning about acceptance in established fragments of the central structured argumentation formalism of ASPIC+. We provide a non-trivial generalization of these recent results, capturing preferences in ASPIC+. In particular, considerin...
Article
We study a model of preference revision in which a prior preference over a set of alternatives is adjusted in order to accommodate input from an authoritative source, while maintaining certain structural constraints (e.g., transitivity, completeness), and without giving up more information than strictly necessary. We analyze this model under two as...
Article
dialectical frameworks (ADFs) constitute one of the most powerful formalisms in abstract argumentation. Their high computational complexity poses, however, certain challenges when designing efficient systems. In this paper, we tackle this issue by (i) analyzing the complexity of ADFs under structural restrictions, (ii) presenting novel algorithms w...
Preprint
Full-text available
We look at preference change arising out of an interaction between two elements: the first is an initial preference ranking encoding a pre-existing attitude; the second element is new preference information signaling input from an authoritative source, which may come into conflict with the initial preference. The aim is to adjust the initial prefer...
Article
Full-text available
Assumption-based argumentation (ABA) is a central structured argumentation formalism. As shown recently, answer set programming (ASP) enables efficiently solving NP-hard reasoning tasks of ABA in practice, in particular in the commonly studied logic programming fragment of ABA. In this work, we harness recent advances in incremental ASP solving for...
Preprint
In this solver description we present ASPARTIX-V, in its 2021 edition, which participates in the International Competition on Computational Models of Argumentation (ICCMA) 2021. ASPARTIX-V is capable of solving all classical (static) reasoning tasks part of ICCMA'21 and extends the ASPARTIX system suite by incorporation of recent ASP language const...
Conference Paper
Argumentation in Artificial Intelligence (AI) builds on formal approaches to reasoning argumentatively. Common to many such approaches is to use argumentation frameworks (AFs) as reasoning engines, with AFs being composed of arguments and attacks between arguments, which are instantiated from knowledge bases in a principle-based manner. While repre...
Preprint
Assumption-based argumentation (ABA) is a central structured argumentation formalism. As shown recently, answer set programming (ASP) enables efficiently solving NP-hard reasoning tasks of ABA in practice, in particular in the commonly studied logic programming fragment of ABA. In this work, we harness recent advances in incremental ASP solving for...
Article
Full-text available
Within argumentation dynamics, a major strand of research is concerned with how changing an argumentation framework affects the acceptability of arguments, and how to modify an argumentation framework in order to guarantee that some arguments have a given acceptance status. In this chapter, we overview the main approaches for enforcement in formal...
Article
The study of computational models for argumentation is a vibrant area of artificial intelligence and, in particular, knowledge representation and reasoning research. Arguments most often have an intrinsic structure made explicit through derivations from more basic structures. Computational models for structured argumentation enable making the inter...
Article
Preferences play a key role in computational argumentation in AI, as they reflect various notions of argument strength vital for the representation of argumentation. Within central formal approaches to structured argumentation, preferential approaches are applied by lifting preferences over defeasible elements to rankings over sets of defeasible el...
Article
argumentation constitutes both a major research strand and a key approach that provides the core reasoning engine for a multitude of formalisms in computational argumentation in AI. Reasoning in abstract argumentation is carried out by viewing arguments and their relationships as abstract entities, with argumentation frameworks (AFs) being the most...
Conference Paper
Abstract argumentation constitutes both a major research strand and a key approach that provides the core reasoning engine for a multitude of formalisms in computational argu-mentation in AI. Reasoning in abstract argumentation is carried out by viewing arguments and their relationships as abstract entities, with argumentation frameworks (AFs) bein...
Conference Paper
A major research direction in AI argumentation is the study and development of practical computational techniques for reasoning in different argumentation formalisms. Compared to abstract argumentation, developing algorithmic techniques for different structured argumentation formalisms, such as assumption-based argumentation and the general ASPIC+...
Article
In this paper we introduce proportionality to belief merging. Belief merging is a framework for aggregating information presented in the form of propositional formulas, and it generalizes many aggregation models in social choice. In our analysis, two incompatible notions of proportionality emerge: one similar to standard notions of proportionality...
Chapter
We present ASPARTIX-V, a tool for reasoning in abstract argumentation frameworks that is based on answer-set programming (ASP), in its 2019 release. ASPARTIX-V participated in this year’s edition of the International Competition on Computational Models of Argumentation (ICCMA’19) in all classical (static) reasoning tasks. In this paper we discuss e...
Article
Argumentation is today a topical area of artificial intelligence (AI) research. Abstract argumentation, with argumentation frameworks (AFs) as the underlying knowledge representation formalism, is a central viewpoint to argumentation in AI. Indeed, from the perspective of AI and computer science, understanding computational and representational asp...
Article
Full-text available
Many recent studies of dynamics in formal argumentation within AI focus on the well-known formalism of Dung’s argumentation frameworks (AFs). Despite the usefulness of AFs in many areas of argumentation, their abstract notion of arguments creates a barrier for operators that modify a given AF, e.g., in the case that dependencies between arguments h...
Article
Focusing on assumption-based argumentation (ABA) as a central structured formalism to AI argumentation, we propose a new approach to reasoning in ABA with and without preferences. While previous approaches apply either specialized algorithms or translate ABA reasoning to reasoning over abstract argumentation frameworks, we develop a direct approach...
Article
We survey a selection of inconsistency measures from the literature and investigate their computational complexity wrt. decision problems related to bounds on the inconsistency value and the functional problem of determining the actual value. Our findings show that those inconsistency measures can be partitioned into four classes related to their c...
Chapter
Automated reasoning techniques for multi-agent scenarios need to address the possibility that procedures for collective decision making may fall prey to manipulation by self-interested agents. In this paper we study manipulation in the context of belief merging, a framework for aggregating agents’ positions, or beliefs, with respect to a set of iss...
Conference Paper
dialectical frameworks (ADFs) constitute one of the most powerful formalisms in abstract argumentation. Their high computational complexity poses, however, certain challenges when designing efficient systems. In this paper, we tackle this issue by (i) analyzing the complexity of ADFs under structural restrictions, (ii) presenting novel algorithms w...
Conference Paper
We study a type of change on knowledge bases inspired by the dynamics of formal argumentation systems, where the goal is to enforce acceptance of certain arguments. We put forward that enforcing acceptance of arguments can be viewed as a member of the wider family of belief change operations, and that an axiomatic treatment of it is therefore desir...
Preprint
Full-text available
Dialectical Frameworks (ADFs) generalize Dung's argumentation frameworks allowing various relationships among arguments to be expressed in a systematic way. We further generalize ADFs so as to accommodate arbitrary acceptance degrees for the arguments. This makes ADFs applicable in domains where both the initial status of arguments and their relati...
Article
Dialectical Frameworks (ADFs) generalize Dung's argumentation frameworks allowing various relationships among arguments to be expressed in a systematic way. We further generalize ADFs so as to accommodate arbitrary acceptance degrees for the arguments. This makes ADFs applicable in domains where both the initial status of arguments and their relati...
Article
Full-text available
Solvers are a quite recent method to uniformly describe algorithms in a rigorous formal way via graphs. Compared to traditional methods like pseudo-code descriptions, abstract solvers have several advantages. In particular, they provide a uniform formal representation that allows for precise comparisons of different algorithms. Recently, this new m...
Article
Argumentation is an active area of modern artificial intelligence (AI) research, with connections to a range of fields, from computational complexity theory and knowledge representation and reasoning to philosophy and social sciences, as well as application-oriented work in domains such as legal reasoning, multi-agent systems, and decision support....
Conference Paper
We study the applicability of abstract argumentation (AF) reasoners in efficiently answering acceptability queries over assumption-based argumentation (ABA) frameworks, one of the prevalent forms of structured argumentation. We provide a refined algorithm for translating ABA frameworks to AFs allowing the use of AF reasoning to answer ABA acceptabi...
Conference Paper
In this paper we describe Pakota, a system implementation that allows for solving enforcement problems over argumentation frameworks. Via harnessing Boolean satisfiability (SAT) and maximum satisfiability (MaxSAT) solvers, Pakota implements algorithms for extension and status enforcement under various central AF semantics, covering a range of NP-co...
Conference Paper
Full-text available
We survey a selection of inconsistency measures from the literature and investigate their computational complexity wrt. decision problems related to bounds on the inconsistency value and the functional problem of determining the actual value. Our findings show that those inconsistency measures can be partitioned into three classes related to their...
Article
Understanding the dynamics of argumentation frameworks (AFs) is important in the study of argumentation in AI. In this work, we focus on the so-called extension enforcement problem in abstract argumentation. We provide a nearly complete computational complexity map of fixed-argument extension enforcement under various major AF semantics, with resul...
Article
The design of efficient solutions for abstract argumentation problems is a crucial step towards advanced argumentation systems. One of the most prominent approaches in the literature is to use Answer-Set Programming (ASP) for this endeavor. In this paper, we present new encodings for three prominent argumentation semantics using the concept of cond...
Chapter
This paper reconsiders Modgil’s Extended Argumentation Frameworks (EAFs) that extend Dung’s abstract argumentation frameworks by attacks on attacks. This allows to encode preferences directly in the framework and thus also to reason about the preferences themselves. As a first step to reduction-based approaches to implement EAFs, we give an alterna...
Conference Paper
solvers are a quite recent method to uniformly describe algorithms in a rigorous formal way and have proven successful in declarative paradigms such as Propositional Satisfiability and Answer Set Programming. In this paper, we apply this machinery for the first time to a dedicated AI formalism, namely Dung’s abstract argumentation frameworks. We pr...
Article
Full-text available
Within the last decade, abstract argumentation has emerged as a central field in Artificial Intelligence. Besides providing a core formalism for many advanced argumentation systems, abstract argumentation has also served to capture several non-monotonic logics and other AI related principles. Although the idea of abstract argumentation is appealing...
Conference Paper
Abstract dialectical frameworks (ADFs) constitute a recent and powerful generalization of Dung's argumentation frameworks (AFs), where the relationship between the arguments is specified via Boolean formulas. Recent results have shown that this enhancement comes with the price of higher complexity compared to AFs. In fact, acceptance problems in th...
Conference Paper
Answer Set Programming is a well-established paradigm of declarative programming in close relationship with other declarative formalisms such as SAT Modulo Theories, Constraint Handling Rules, PDDL and many others. Since its first informal editions, ASP systems are compared in the nowadays customary ASP Competition. The fourth ASP Competition, held...
Conference Paper
System competitions evaluate solvers and compare state-of-the-art implementations on benchmark sets in a dedicated and controlled computing environment comprising of multiple hosts. An important task for running a competition is the benchmark execution platform that schedules the workload on available benchmark machines, keeps track of failed and f...
Conference Paper
Answer set programming (ASP) is nowadays one of the most popular modeling languages in the areas of Knowledge Representation and Artificial Intelligence. Hereby one represents the problem at hand in such a way that each model of the ASP program corresponds to one solution of the original problem. In recent years, several tools which support the use...
Conference Paper
Full-text available
The aim of this paper is to study the concept of admissibility in abstract dialectical frameworks (ADFs). While admissibility is well-understood in Dung-style frameworks, a generalization to ADFs is not trivial. Indeed, the original proposal turned out to behave unintuitively at certain instances. A recent approach circumvented this problem by usin...
Article
In the context of the emerging Semantic Web and the quest for a common logical framework underpinning its architecture, the relation of rule-based languages such as Answer Set Programming (ASP) and ontology languages such as the Web Ontology Language (OWL) has attracted a lot of attention in the literature over the past years. With its roots in Ded...
Article
Within the area of computational models of argumentation, the instantiation-based approach is gaining more and more attention, not at least because meaningful input for Dung's abstract frameworks is provided in that way. In a nutshell, the aim of instantiation-based argumentation is to form, from a given knowledge base, a set of arguments and to id...
Conference Paper
Abstract argumentation frameworks (AFs) provide the basis for various reasoning problems in the areas of Knowledge Representation and Artificial Intelligence. Efficient evaluation of AFs has thus been identified as an important research challenge. So far, implemented systems for evaluating AFs have either followed a straight-forward reduction-based...
Article
Random testing is a valuable supplement to systematic test methods because it discovers defects that are very hard to detect with systematic test strategies. We propose a novel approach for random test generation that combines the benefits of model-based testing, constraint satisfaction, and pure random testing. The proposed method has been incorpo...

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