Computing ideal sceptical argumentation

We present two dialectic procedures for the sceptical ideal semantics for argumentation. The first procedure is defined in terms of dispute trees, for abstract argumentation frameworks. The second procedure is defined in dialectical terms, for assumption-based argumentation frameworks. The procedures are adapted from (variants of) corresponding procedures for computing the credulous admissible semantics for assumption-based argumentation, proposed in [P.M. Dung, R.A. Kowalski, F. Toni, Dialectic proof procedures for assumption-based, admissible argumentation, Artificial Intelligence 170 (2006) 114–159]. We prove that the first procedure is sound and complete, and the second procedure is sound in general and complete for a special but natural class of assumption-based argumentation frameworks, that we refer to as p-acyclic. We also prove that in the case of p-acyclic assumption-based argumentation frameworks (a variant of) the procedure of [P.M. Dung, R.A. Kowalski, F. Toni, Dialectic proof procedures for assumption-based, admissible argumentation, Artificial Intelligence 170 (2006) 114–159] for the admissible semantics is complete. Finally, we present a variant of the procedure of [P.M. Dung, R.A. Kowalski, F. Toni, Dialectic proof procedures for assumption-based, admissible argumentation, Artificial Intelligence 170 (2006) 114–159] that is sound for the sceptical grounded semantics.     

Probabilistic Argumentation Systems and Abduction

Probabilistic argumentation systems are based on assumption-based reasoning for obtaining arguments supporting hypotheses and on probability theory to compute probabilities of supports. Assumption-based reasoning is closely related to hypothetical reasoning or inference through theory formation. The latter approach has well known relations to abduction and default reasoning. In this paper assumption-based reasoning, as an alternative to theory formation aiming at a different goal, will be presented and its use for abduction and model-based diagnostics will be explained. Assumption-based reasoning is well suited for defining a probability structure on top of it. On the base of the relationships between assumption-based reasoning on the one hand and abduction on the other hand, the added value introduced by probability into model based diagnostics will be discussed. Furthermore, the concepts of complete and partial models are introduced with the goal to study the quality of inference procedures. In particular this will be used to compare abductive to possible explanations.     

Dialectic proof procedures for assumption-based, admissible argumentation

We present a family of dialectic proof procedures for the admissibility semantics of assumption-based argumentation. These proof procedures are defined for any conventional logic formulated as a collection of inference rules and show how any such logic can be extended to a dialectic argumentation system.The proof procedures find a set of assumptions, to defend a given belief, by starting from an initial set of assumptions that supports an argument for the belief and adding defending assumptions incrementally to counter-attack all attacks.The proof procedures share the same notion of winning strategy for a dispute and differ only in the search strategy they use for finding it. The novelty of our approach lies mainly in its use of backward reasoning to construct arguments and potential arguments, and the fact that the proponent and opponent can attack one another before an argument is completed. The definition of winning strategy can be implemented directly as a non-deterministic program, whose search strategy implements the search for defences.     

On Construction and Evaluation of Analogical Arguments for Persuasive Reasoning

ABSTRACT

Analogical reasoning is a complex process based on a comparison between two pairs of concepts or states of affairs (aka. the source and the target) for characterizing certain features from one to another. Arguments which employ this process to support their claims are called analogical arguments. Our goals are to study the structure and the computation for their defeasibility in light of the argumentation theory. Our proposed assumption-based argumentation with predicate similarity ABA^(p) framework can be seen as an extension of assumption-based argumentation framework (ABA), in which not only assumptions can be used but also similarity of predicates is used to support a claim. ABA ^(p) labels each argument tree with an analogical degree and different ways to aggregate numerical values are studied toward gullible/skeptical characteristics in agent reasoning. The acceptability of analogical arguments is evaluated w.r.t. the semantics of abstract argumentation. Finally, we demonstrate that ABA ^(p) captures the argumentation scheme for argument from analogy and provides an explanation when it is used for persuasion.     

Towards a Formal Account of Reasoning about Evidence: Argumentation Schemes and Generalisations

This paper studies the modelling of legal reasoning about evidence within general theories of defeasible reasoning and argumentation. In particular, Wigmore's method for charting evidence and its use by modern legal evidence scholars is studied in order to give a formal underpinning in terms of logics for defeasible argumentation. Two notions turn out to be crucial, viz. argumentation schemes and empirical generalisations.     

A taxonomy of argumentation models used for knowledge representation

Understanding argumentation and its role in human reasoning has been a continuous subject of investigation for scholars from the ancient Greek philosophers to current researchers in philosophy, logic and artificial intelligence. In recent years, argumentation models have been used in different areas such as knowledge representation, explanation, proof elaboration, commonsense reasoning, logic programming, legal reasoning, decision making, and negotiation. However, these models address quite specific needs and there is need for a conceptual framework that would organize and compare existing argumentation-based models and methods. Such a framework would be very useful especially for researchers and practitioners who want to select appropriate argumentation models or techniques to be incorporated in new software systems with argumentation capabilities. In this paper, we propose such a conceptual framework, based on taxonomy of the most important argumentation models, approaches and systems found in the literature. This framework highlights the similarities and differences between these argumentation models. As an illustration of the practical use of this framework, we present a case study which shows how we used this framework to select and enrich an argumentation model in a knowledge acquisition project which aimed at representing argumentative knowledge contained in texts critiquing military courses of action.     

辩论的逻辑模型研究综述

辩论的逻辑模型是哲学、逻辑学和人工智能等多个领域的研究课题,在非单调推理、法律推理、决策支持和多Agent交互等领域有广泛应用。文中首先简要阐述辩论及辩论模型的基本概念。然后从对辩论建模和用辩论建模两个方面对目前的研究进行总结,分析现有的有影响的辩论模型特点及其存在的问题。最后,指出今后的研究方向和发展趋势。     

一种基于主体可信度的联合辩论框架

辩论框架是计算机利用辩论机制来解决实际问题的基础,如商务谈判、法律纠纷和劳动争议等。传统的辩论框架对辩论机制和论证方法作了具体的形式化描述,但忽略了辩论主体及其对辩论结果影响的描述,而且在辩论过程中一个论点通常需要多个论据的联合论证。针对以上问题,在传统辩论框架的基础上,提出了一种基于主体可信度的联合辩论框架(STUAF)。首先引入了辩论主体的概念,并对观点和论据之间的联合论证进行形式化定义;其次给出了完整的框架结构和语义描述,证明了该辩论框架满足Dunk提出的标准辩论框架的基本定理;然后结合辩论树给出了语义计算的算法;最后给出一个具体的应用实例,实例分析表明S I'UAF及其语义算法是有效的。     

Formalizing dialectical explanation support for argument-based reasoning in knowledge-based systems

The concept of explanation has received attention from different areas in Computer Science, particularly in the knowledge-based systems and expert systems communities. At the same time, argumentation has evolved as a new paradigm for conceptualizing commonsense reasoning, resulting in the formalization of different argumentation frameworks and the development of several real-world argument-based applications. Although the notions of explanation and argument for a claim share many common elements in knowledge-based systems their interrelationships have not yet been formally studied in the context of the current argumentation research in Artificial Intelligence. This article explores these ideas by providing a new perspective on how to formalize dialectical explanation support for argument-based reasoning. To do this, we propose a formalization of explanations for abstract argumentation frameworks with dialectical constraints where different emerging properties are studied and analyzed. As a concrete example of the formalism introduced we show how it can be fleshed out in an implemented rule-based argumentation system.     

Computing Arguments and Attacks in Assumption-Based Argumentation

Most computational frameworks for argumentation are based on abstract argumentation, which determines an argument's acceptability on the basis of its ability to counterattack all arguments attacking it. However, this view of argumentation doesn't address how to find arguments, identify attacks, and exploit premises. Assumption-based argumentation addresses these three issues. It's a refinement of abstract argumentation but remains general purpose, nonetheless. Rather than considering arguments to be a primitive concept, assumption-based argumentation defines them as backward deductions (using sets of rules in an underlying logic) supported by sets of assumptions. This approach reduces the notion of an attack against an argument to that of deduction of a contrary of an assumption.     

Legal Case-based Reasoning as Practical Reasoning

In this paper we apply a general account of practical reasoning to arguing about legal cases. In particular, we provide a reconstruction of the reasoning of the majority and dissenting opinions for a particular well-known case from property law. This is done through the use of Belief-Desire-Intention (BDI) agents to replicate the contrasting views involved in the actual decision. This reconstruction suggests that the reasoning involved can be separated into three distinct levels: factual and normative levels and a level connecting the two, with conclusions at one level forming premises at the next. We begin by summarising our general approach, which uses instantiations of an argumentation scheme to provide presumptive justifications for actions, and critical questions to identify arguments which attack these justifications. These arguments and attacks are organised into argumentation frameworks to identify the status of individual arguments. We then discuss the levels of reasoning that occur in this reconstruction and the properties and significance of each of these levels. We illustrate the different levels with short examples and also include a discussion of the role of precedents within these levels of reasoning.     

A formal model of adjudication dialogues

This article presents a formal dialogue game for adjudication dialogues. Existing AI & law models of legal dialogues and argumentation-theoretic models of persuasion are extended with a neutral third party, to give a more realistic account of the adjudicator’s role in legal procedures. The main feature of the model is a division into an argumentation phase, where the adversaries plea their case and the adjudicator has a largely mediating role, and a decision phase, where the adjudicator decides the dispute on the basis of the claims, arguments and evidence put forward in the argumentation phase. The model allows for explicit decisions on admissibility of evidence and burden of proof by the adjudicator in the argumentation phase. Adjudication is modelled as putting forward arguments, in particular undercutting and priority arguments, in the decision phase. The model reconciles logical aspects of burden of proof induced by the defeasible nature of arguments with dialogical aspects of burden of proof as something that can be allocated by explicit decisions on legal grounds.

ASSUMPTION-BASED REASONING AND CLAUSE MANAGEMENT SYSTEMS

A truth maintenance system is a subsystem that manages the utilization of assumptions in the reasoning process of a problem solver. Doyle's original motivation for creating a truth maintenance system was to augment a reasoning system with a control strategy for activities concerning its nonmonotonic state of beliefs. Hitherto, much effort has been invested in designing and implementing the concept of truth maintenance, and little effort has been dedicated to the formalization that is essential to understanding it. This paper provides a complete formalization of the principle of truth maintenance. Motivated by Reiter and de Kleer's preliminary report on the same subject, this paper extends their study and gives a formal account of the concept of truth maintenance under the general title of assumption-based reasoning. The concept of assumption-based theory is defined, and the notions of explanation and direct consequence are presented as forms of plausible conclusions with respect to this theory. Additionally, the concepts of extension and irrefutable sentences are discussed together with other variations of explanation and direct consequence. A set of algorithms for computing these conclusions for a given theory are presented using the notion of prime implicates. Finally, an extended example on Boolean circuit diagnosis is shown to exemplify these ideas.     

Rules and Principles in Legal Reasoning. A Study of Vagueness and Collisions in Artificial Intelligence and Law

There is a difference between rules and principles in Law Argumentation Theory. The conflict of rules is solved by meta-rules like Lex Superior (based in general hierarchical structure of legal system), Lex Posterior (based on later rule priority), Lex Specialis (based on specification of rules) and also by exceptions, which exclude the conflict. The collisions of rules imply the validity negation of one rule. However, this does not occur in a collision of principles. Even when one principle is not applied by collisions, its validity remains. Another point is that the priority could change, changing the overridden principle. So, it is necessary to build a reasoning model that allows reasoning with conflicting legal principles. Another problem is vagueness of principles. Vagueness does not mean just an imprecise meaning, linguistically talking. There should be attributed a semantic, or a pragmatic meaning. Vagueness of principles occurs on account of its opened antecedent, with no established conduct. In this paper a model of reasoning using Artificial Intelligence (AI) & Law methods is described aiming at treating vagueness and collisions of principles, searching to establish rationality in legal argumentation systems.     

Persuasion Dialogue in Online Dispute Resolution

In this paper we show how dialogue-based theories of argumentation can contribute to the construction of effective systems of dispute resolution. Specifically we consider the role of persuasion in online dispute resolution by showing how persuasion dialogues can be functionally embedded in negotiation dialogues, and how negotiation dialogues can shift to persuasion dialogues. We conclude with some remarks on how persuasion dialogues might be modelled is such a way as to allow them to be implemented in a mechanical or computerized system of dialogue or dialogue management.     

Nonmonotonic reasoning as prioritized argumentation

This paper proposes a formalism for nonmonotonic reasoning based on prioritized argumentation. We argue that nonmonotonic reasoning in general can be viewed as selecting monotonic inferences by a simple notion of priority among inference rules. More importantly, these types of constrained inferences can be specified in a knowledge representation language where a theory consists of a collection of rules of first order formulas and a priority among these rules. We recast default reasoning as a form of prioritized argumentation and illustrate how the parameterized formulation of priority may be used to allow various extensions and modifications to default reasoning. We also show that it is possible, but more difficult, to express prioritized argumentation by default logic: Even some particular forms of prioritized argumentation cannot be represented modularly by defaults under the same language     

Dialectical Argumentation with Argumentation Schemes: An Approach to Legal Logic

This paper describes an approach to legal logic based on the formal analysis of argumentation schemes. Argumentation schemes a notion borrowed from the .eld of argumentation theory - are a kind of generalized rules of inference, in the sense that they express that given certain premises a particular conclusion can be drawn. However, argumentation schemes need not concern strict, abstract, necessarily valid patterns of reasoning, but can be defeasible, concrete and contingently valid, i.e., valid in certain contexts or under certain circumstances. A method is presented to analyze argumentation schemes and it is shown how argumentation schemes can be embedded in a formal model of dialectical argumentation.     

Digital technologies and artificial intelligence’s present and foreseeable impact on lawyering,judging, policing and law enforcement

‘AI & Law’ research has been around since the 1970s, even though with shifting emphasis. This is an overview of the contributions of digital technologies, both artificial intelligence and non-AI smart tools, to both the legal professions and the police. For example, we briefly consider text mining and case-automated summarization, tools supporting argumentation, tools concerning sentencing based on the technique of case-based reasoning, the role of abductive reasoning, research into applying AI to legal evidence, tools for fighting crime and tools for identification.