Floris Bex

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, Wigmores 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 hybrid formal theory of arguments, stories and criminal evidence

This paper presents a theory of reasoning with evidence in order to determine the facts in a criminal case. The focus is on the process of proof, in which the facts of the case are determined, rather than on related legal issues, such as the admissibility of evidence. In the literature, two approaches to reasoning with evidence can be distinguished, one argument-based and one story-based. In an argument-based approach to reasoning with evidence, the reasons for and against the occurrence of an event, e.g., based on witness testimony, are central. In a story-based approach, evidence is evaluated and interpreted from the perspective of the factual stories as they may have occurred in a case, e.g., as they are defended by the prosecution. In this paper, we argue that both arguments and narratives are relevant and useful in the reasoning with and interpretation of evidence. Therefore, a hybrid approach is proposed and formally developed, doing justice to both the argument-based and the narrative-based perspective. By the formalization of the theory and the associated graphical representations, our proposal is the basis for the design of software developed as a tool to make sense of the evidence in complex cases.

Implementing the argument web

Improve online public discourse by connecting opinions across blogs, editorials, and social media.

The Added Value of Argumentation

We discuss the value of argumentation in reaching agreements, based on its capability for dealing with conflicts and uncertainty. Logic-based models of argumentation have recently emerged as a key topic within Artificial Intelligence. Key reasons for the success of these models is that they are akin to human models of reasoning and debate, and their generalisation to frameworks for modelling dialogues. They therefore have the potential for bridging between human and machine reasoning in the presence of uncertainty and conflict. We provide an overview of a number of examples that bear witness to this potential, and that illustrate the added value of argumentation. These examples amount to methods and techniques for argumentation to aid machine reasoning (e.g. in the form of machine learning and belief functions) on the one hand and methods and techniques for argumentation to aid human reasoning (e.g. for various forms of decision making and deliberation and for the Web) on the other. We also identify a number of open challenges if this potential is to be realised, and in particular the need for benchmark libraries.

Did he jump or was he pushed?: abductive practical reasoning

In this paper, we present a particular role for abductive reasoning in law by applying it in the context of an argumentation scheme for practical reasoning. We present a particular scheme, based on an established scheme for practical reasoning, that can be used to reason abductively about how an agent might have acted to reach a particular scenario, and the motivations for doing so. Plausibility here depends on a satisfactory explanation of why this particular agent followed these motivations in the particular situation. The scheme is given a formal grounding in terms of action-based alternating transition systems and we illustrate the approach with a running legal example.

Rationalization of goal models in GRL using formal argumentation

We apply an existing formal framework for practical reasoning with arguments and evidence to the Goal-oriented Requirements Language (GRL), which is part of the User Requirements Notation (URN). This formal framework serves as a rationalization for elements in a GRL model: using attack relations between arguments we can automatically compute the acceptability status of elements in a GRL model, based on the acceptability status of their underlying arguments and the evidence. We integrate the formal framework into the GRL metamodel and we set out a research to further develop this framework.

RationalGRL: A Framework for Rationalizing Goal Models Using Argument Diagrams

Goal modeling languages, such as i* and the Goal-oriented Requirements Language (GRL), capture and analyze high-level goals and their relationships with lower level goals and tasks. However, in such models, the rationalization behind these goals and tasks and the selection of alternatives are usually left implicit. To better integrate goal models and their rationalization, we develop the RationalGRL framework, in which argument diagrams can be mapped to goal models. Moreover, we integrate the result of the evaluation of arguments and their counterarguments with GRL initial satisfaction values. We develop an interface between the argument web tools OVA and TOAST and the Eclipse-based tool for GRL called jUCMNav. We demonstrate our methodology with a case study from the Schiphol Group.

On logical specifications of the Argument Interchange Format

The Argument Interchange Format (AIF) has been devised in order to support the interchange of ideas and data between different projects and applications in the area of computational argumentation. The AIF presents an abstract ontology for argumentation which serves as an interlingua between various reifications that consist of more concrete argumentation languages. In this paper, we aim to give a logical reification of the AIF ontology, by defining translations between the ontology’s language and the formal ASPIC framework for argumentation. We thus lay foundations for interrelating formal logic-based approaches to argumentation captured by the general ASPIC framework, and the wider class of AIF reifications, including those that are more informal and user orientated.

Arguments, Stories and Criminal Evidence

Preface.- Chapter 1. Introduction.- Chapter 2. Reasoning with criminal evidence.- Chapter 3. Two approaches to reasoning with evidence: arguments and stories.- Chapter 4. A hybrid theory of stories and arguments.- Chapter 5. A formal logical hybrid theory of argumentation and explanation.- Chapter 6. Case study: Murder in Anjum.- Chapter 7. Related research on reasoning with criminal evidence.- Chapter 8. Conclusions. - References.- Index.

Formalising argumentative story-based analysis of evidence

In the present paper, we provide a formalised version of a merged argumentative and story-based approach towards the analysis of evidence. As an application, we are able to show how our approach sheds new light on inference to the best explanation with case evidence. More specifically, it will be clarified how the events in a case story that are considered to be proven abductively explain the otherwise unproven events of the case story. We compare our approach with existing AI work on modelling legal reasoning with evidence.