Example of Artificial Intelligence and Law format
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Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format
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Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format Example of Artificial Intelligence and Law format
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Artificial Intelligence and Law — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Law #10 of 722 up up by 51 ranks
Artificial Intelligence #42 of 227 up up by 35 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 63 Published Papers | 471 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 04/07/2020
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Related Journals

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SJR: 2.156
SNIP: 2.402
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Springer

Quality:  
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CiteRatio: 3.2
SJR: 0.921
SNIP: 2.219

Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

A measure of average citations received per peer-reviewed paper published in the journal.

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

7.5

25% from 2019

CiteRatio for Artificial Intelligence and Law from 2016 - 2020
Year Value
2020 7.5
2019 6.0
2018 3.9
2017 2.9
2016 2.7
graph view Graph view
table view Table view

0.856

42% from 2019

SJR for Artificial Intelligence and Law from 2016 - 2020
Year Value
2020 0.856
2019 1.482
2018 0.492
2017 0.937
2016 0.364
graph view Graph view
table view Table view

3.81

48% from 2019

SNIP for Artificial Intelligence and Law from 2016 - 2020
Year Value
2020 3.81
2019 2.573
2018 1.824
2017 1.862
2016 1.542
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has increased by 25% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has decreased by 42% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 48% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Artificial Intelligence and Law

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Springer

Artificial Intelligence and Law

Artificial Intelligence and Law is an international forum for the dissemination of original interdisciplinary research in the following areas: • Theoretical or empirical studies in artificial intelligence (AI), cognitive psychology, jurisprudence, linguistics, or philosophy wh...... Read More

Law

Artificial Intelligence

Social Sciences

i
Last updated on
04 Jul 2020
i
ISSN
0924-8463
i
Impact Factor
High - 1.959
i
Open Access
No
i
Sherpa RoMEO Archiving Policy
Green faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Bibliography Name
SPBASIC
i
Citation Type
Author Year
(Blonder et al, 1982)
i
Bibliography Example
Beenakker CWJ (2006) Specular andreev reflection in graphene. Phys Rev Lett 97(6):067,007, URL 10.1103/PhysRevLett.97.067007

Top papers written in this journal

Journal Article DOI: 10.1023/A:1008319631231
An ontology for commitments in multiagent systems
Munindar P. Singh1

Abstract:

Social commitments have long been recognized as an important concept for multiagent systems. We propose a rich formulation of social commitments that motivates an architecture for multiagent systems, which we dub spheres of commitment. We identify the key operations on commitments and multiagent systems. We distinguish betwee... Social commitments have long been recognized as an important concept for multiagent systems. We propose a rich formulation of social commitments that motivates an architecture for multiagent systems, which we dub spheres of commitment. We identify the key operations on commitments and multiagent systems. We distinguish between explicit and implicit commitments. Multiagent systems, viewed as spheres of commitment (SoComs), provide the context for the different operations on commitments. Armed with the above ideas, we can capture normative concepts such as obligations, taboos, conventions, and pledges as different kinds of commitments. In this manner, we synthesize ideas from multiagent systems, particularly the idea of social context, with ideas from ethics and legal reasoning, specifically that of directed obligations in the Hohfeldian tradition. read more read less
View PDF
361 Citations
Journal Article DOI: 10.1007/BF00118496
A dialectical model of assessing conflicting arguments in legal reasoning
Henry Prakken1, Giovanni Sartor2

Abstract:

Inspired by legal reasoning, this paper presents a formal framework for assessing conflicting arguments. Its use is illustrated with applications to realistic legal examples, and the potential for implementation is discussed. The framework has the form of a logical system for defeasible argumentation. Its language, which is o... Inspired by legal reasoning, this paper presents a formal framework for assessing conflicting arguments. Its use is illustrated with applications to realistic legal examples, and the potential for implementation is discussed. The framework has the form of a logical system for defeasible argumentation. Its language, which is of a logic-programming-like nature, has both weak and explicit negation, and conflicts between arguments are decided with the help of priorities on the rules. An important feature of the system is that these priorities are not fixed, but are themselves defeasibly derived as conclusions within the system. Thus debates on the choice between conflicting arguments can also be modelled. The proof theory of the system is stated in dialectical style, where a proof takes the form of a dialogue between a proponent and an opponent of an argument. An argument is shown to be justified if the proponent can make the opponent run out of moves in whatever way the opponent attacks. Despite this dialectical form, the system reflects a `declarative', or `relational' approach to modelling legal argument. A basic assumption of this paper is that this approach complements two other lines of research in AI and Law, investigations of precedent-based reasoning and the development of `procedural', or `dialectical' models of legal argument. read more read less

Topics:

Argument (64%)64% related to the paper, Artificial intelligence and law (59%)59% related to the paper, Defeasible reasoning (55%)55% related to the paper, Argumentation theory (54%)54% related to the paper, Philosophy of law (52%)52% related to the paper
355 Citations
Journal Article DOI: 10.1023/A:1008315530323
Autonomous agents with norms
Frank Dignum1

Abstract:

In this paper we present some concepts and their relations that are necessary for modeling autonomous agents in an environment that is governed by some (social) norms. We divide the norms over three levels: the private level the contract level and the convention level. We show how deontic logic can be used to model the concep... In this paper we present some concepts and their relations that are necessary for modeling autonomous agents in an environment that is governed by some (social) norms. We divide the norms over three levels: the private level the contract level and the convention level. We show how deontic logic can be used to model the concepts and how the theory of speech acts can be used to model the generation of (some of) the norms. Finally we give some idea about an agent architecture incorporating the social norms based on a BDI framework. read more read less

Topics:

Deontic logic (63%)63% related to the paper, Convention (60%)60% related to the paper, Autonomous agent (59%)59% related to the paper, Agent architecture (53%)53% related to the paper
261 Citations
Journal Article DOI: 10.1007/BF00871972
The Pleadings Game: an exercise in computational dialectics

Abstract:

The Pleadings Game is a normative formalization and computational model of civil pleading, founded in Roberty Alexy's discourse theory of legal argumentation. The consequences of arguments and counterarguments are modelled using Geffner and Pearl's nonmonotonic logic,conditional entailment. Discourse in focussed using the con... The Pleadings Game is a normative formalization and computational model of civil pleading, founded in Roberty Alexy's discourse theory of legal argumentation. The consequences of arguments and counterarguments are modelled using Geffner and Pearl's nonmonotonic logic,conditional entailment. Discourse in focussed using the concepts of issue and relevance. Conflicts between arguments can be resolved by arguing about the validity and priority of rules, at any level. The computational model is fully implemented and has been tested using examples from Article Nine of the Uniform Commercial Code. read more read less

Topics:

Pleading (53%)53% related to the paper, Argumentation theory (52%)52% related to the paper, Civil procedure (51%)51% related to the paper, Artificial intelligence and law (50%)50% related to the paper
224 Citations
Book Chapter DOI: 10.1007/978-94-015-9010-5_5
Modelling Reasoning with Precedents in a Formal Dialogue Game
Henry Prakken1, Giovanni Sartor2

Abstract:

This paper analyses legal reasoning with precedents in the setting of a formally defined dialogue game. After giving a legal-theoretical account of judicial reasoning with precedents, a formal method is proposed for representing precedents and it is discussed how such representations can be used in a formally defined dialecti... This paper analyses legal reasoning with precedents in the setting of a formally defined dialogue game. After giving a legal-theoretical account of judicial reasoning with precedents, a formal method is proposed for representing precedents and it is discussed how such representations can be used in a formally defined dialectical protocol for dispute. The basic ideas are to represent cases as argument structures (including pro and con arguments, and the arguments for adjudicating their conflicts) and to define certain case-based reasoning moves as strategies for introducing information into a dispute. In particular, analogizing and distinguishing are conceived as elementary theory construction moves, which produce new information on the basis of an existing stock of cases. The approach also offers the possibility of using portions of precedents and of expressing criteria for determining the outcome of precedent-based disputes. read more read less

Topics:

Case-based reasoning (61%)61% related to the paper, Artificial intelligence and law (56%)56% related to the paper
212 Citations
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1. Can I write Artificial Intelligence and Law in LaTeX?

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Yes, the template is compliant with the Artificial Intelligence and Law guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Artificial Intelligence and Law?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Artificial Intelligence and Law citation style.

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Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Artificial Intelligence and Law.

5. Can I use a manuscript in Artificial Intelligence and Law that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Artificial Intelligence and Law that you can download at the end.

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7. Where can I find the template for the Artificial Intelligence and Law?

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12. Is Artificial Intelligence and Law's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Artificial Intelligence and Law?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Artificial Intelligence and Law. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Artificial Intelligence and Law?

The 5 most common citation types in order of usage for Artificial Intelligence and Law are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

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16. Can I download Artificial Intelligence and Law in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Artificial Intelligence and Law Endnote style according to Elsevier guidelines.

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