Computational Models, Argumentation Theories and Legal Practice

Bench‐Capon, Trevor; Freeman, James B.; Hohmann, Hanns; Prakken, Henry

doi:10.1007/978-94-017-0431-1_4

Cited by 11 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are a number of particular disciplines in which argumentation is central, and which have particular styles of argument associated with them. One such area which has been the subject of a good deal of argumentation related AI research is Law (see [166] for a survey of AI and Law research, and for overviews of argumentation in AI and Law see [33,34]). Argumentation is particularly important in law: a legal case typically centres on a conflict between two parties which is resolved by each side producing arguments in an effort to persuade the judge that their side is right.…”

Section: Specialist Domains and Applicationsmentioning

confidence: 99%

Argumentation in artificial intelligence

Bench‐Capon

Dunne

2007

Artificial Intelligence

513

274

View full text Add to dashboard Cite

Over the last ten years, argumentation has come to be increasingly central as a core study within Artificial Intelligence (AI). The articles forming this volume reflect a variety of important trends, developments, and applications covering a range of current topics relating to the theory and applications of argumentation. Our aims in this introduction are, firstly, to place these contributions in the context of the historical foundations of argumentation in AI and, subsequently, to discuss a number of themes that have emerged in recent years resulting in a significant broadening of the areas in which argumentation based methods are used. We begin by presenting a brief overview of the issues of interest within the classical study of argumentation: in particular, its relationshipin terms of both similarities and important differences-to traditional concepts of logical reasoning and mathematical proof. We continue by outlining how a number of foundational contributions provided the basis for the formulation of argumentation models and their promotion in AI related settings and then consider a number of new themes that have emerged in recent years, many of which provide the principal topics of the research presented in this volume.

show abstract

Section: Specialist Domains and Applicationsmentioning

confidence: 99%

Argumentation in artificial intelligence

Bench‐Capon

Dunne

2007

Artificial Intelligence

513

274

View full text Add to dashboard Cite

show abstract

“…The evidence gathered, therefore, constitutes a set of defeasible arguments in support of, and in defence of, the complaint. Given this, our approach borrows ideas from computational models of legal reasoning and legal argumentation (14).…”

Section: Policing Within a Vomentioning

confidence: 99%

Delivering services by building and running virtual organisations

Nguyen¹,

Thompson²,

Patel³

et al. 2006

BT Technol J

View full text Add to dashboard Cite

In our view, customers in the future are likely to obtain their services from coalitions of service providers. These coalitions can be described as virtual organisations (VOs); they are group of service providers that form relationships to service customers' demands on an ad-hoc basis. For a VO to be effective, it must be reliable and scalable, and realistically, it must be created and maintained in a dynamic, open and competitive environment. The CONOISE-G project has focused on resolving the technology challenges that emerged from these requirements. Specifically, CONOISE-G provides mechanisms to assure effective operation of VOs in the face of failure, unexpected events and changing requirements in dynamic, open and competitive environment. In this paper, we describe the CONOISE-G system; motivated by a scenario based on mobile service provision; outline its use in the context of VO formation and perturbation and review current efforts to progress the work to deal with unreliable information sources. 1

show abstract

“…Dialogue games have proven extremely useful for modeling various forms of reasoning in many domains[1].…”

mentioning

confidence: 99%

On the Benefits of Argumentation-Derived Evidence in Learning Policies

Emele

Norman

Guérin

et al. 2011

Lecture Notes in Computer Science

View full text Add to dashboard Cite

An important and non-trivial factor for effectively developing and resourcing plans in a collaborative context is an understanding of the policy and resource availability constraints under which others operate. We present an efficient approach for identifying, learning and modeling the policies of others during collaborative problem solving activities. The mechanisms presented in this paper will enable agents to build more effective argumentation strategies by keeping track of who might have, and be willing to provide the resources required for the enactment of a plan. We argue that agents can improve their argumentation strategies by building accurate models of others' policies regarding resource use, information provision, etc. In a set of experiments, we demonstrate the utility of this novel combination of techniques through empirical evaluation, in which we demonstrate that more accurate models of others' policies (or norms) can be developed more rapidly using various forms of evidence from argumentation-based dialogue.

show abstract

Computational Models, Argumentation Theories and Legal Practice

Cited by 11 publications

References 0 publications

Argumentation in artificial intelligence

Argumentation in artificial intelligence

Delivering services by building and running virtual organisations

On the Benefits of Argumentation-Derived Evidence in Learning Policies

Contact Info

Product

Resources

About