Changes for page Arg2P

From version 45.1
edited by Andrea Omicini
on 03/11/2021 16:22
Change comment: There is no comment for this version
To version 26.1
edited by Roberta Calegari
on 13/03/2021 07:37
Change comment: There is no comment for this version

Summary

Details

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1 -Arg2P Home
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1 -(% style="background-color:$theme.fieldGradientColor" %)(((
2 -!!{{arg2p/}} (short for {{argtuprolog/}}) is a logic-based agreement framework enabling defeasible reasoning in intelligent systems
3 -)))
4 -== {{arg2p/}} in a nutshell ==
1 +{{include document="MacroSheet"/}}
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6 -The {{arg2p/}} argumentation engine is built on the top of [[{{tuprolog/}}>>Tuprolog.WebHome||target=_blank]] ({{2p/}}) engine. {{arg2p/}} is a lightweight implementation of the ASPIC+-like system for structured argumentation.
3 +{{summary}}{{arg2p/}} is logic-based agreement framework enabling defeasible reasoning and agents conversation in AI applications so particularly suitable for reaching agents’ explainable intelligent behaviours.{{/summary}}
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8 -{{arg2p/}} enables defeasible reasoning and argumentation, and deals with priorities over rules. It includes a formal method for dealing with burden of proof (//burden of persuasion//).
5 +== {{arg2p/}} in a nutshell ==
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10 -More informations on the project are available on the {{arg2p/}} [[GitLab wiki>>https://pika-lab.gitlab.io/argumentation/arg2p-kt/]].
7 +The {{arg2p/}} argumentation engine is built on the top of {{tuprolog/}} ({{2p/}}) engine. {{arg2p/}} is a lightweight implementation of the ASPIC+-like system for structured argumentation.
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12 -{{include reference="Environment"/}}
9 +In {{arg2p/}} arguments are produced from a set of defeasible rules, and attack relationships between arguments are captured by argumentation graphs. The arguments of such graphs are labelled by following a labelling semantics. This simple framework will suffice to illustrate our upcoming investigation into persuasive burdens within an argumentation setting.
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11 +In addition, we use defeasible rule schemata to account for deontic reasoning, towards doctrine reification, as presented in Riveret et al., 2019.
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13 +Moreover, the model has been extended following the burden of proof model presented in [[Calegari and Sartor, 2020>>Publications.BurdenofproofIclp2020]].
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15 +More information about the format of the knowledge base and rules can be found on the basic syntax.

Contacts

Roberta Calegari email  |  Giovanni Ciatto email  |  Andrea Omicini email  |  Giuseppe Pisano email  |  Giovanni Sartor email

Downloads

GitHub  |  Maven Central  |  NPM

Documentation

GitLab

Online tools

Playground

Sources

GitHub