Changes for page Arg2P

Summary

• Page properties (3 modified, 0 added, 0 removed)

Details

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Title

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1		-Arg2P Home
	1	+Arg2P

Author

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1		-XWiki.AndreaOmicini
	1	+XWiki.RobertaCalegari

Content

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1		->{{arg2p/}} is logic-based agreement framework enabling defeasible reasoning and agents’ conversation in AI applications so particularly suitable for reaching agents’ explainable intelligent behaviours
	1	+{{include document="MacroSheet"/}}
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	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}}
	4	+
3	3	== {{arg2p/}} in a nutshell ==
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5		-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.
	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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7		-In {{arg2p/}} arguments are produced from a set of defeasible rules possibly containing deontic statements, and attack relationships between arguments are captured by argumentation graphs. The arguments of such graphs are labelled by following standard Dung's labelling semantics.
	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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9		-The model has been extended following the burden of proof model and semantics presented in [[Calegari and Sartor, 2020>>Publications.BurdenofproofIclp2020]].
	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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11		-More informations on the project are available on the official {{arg2p/}} [[wiki>>https://pika-lab.gitlab.io/argumentation/arg2p-kt/]].
	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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13		-{{include reference="Arg2p.MacroSheet"/}}
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	15	+More information about the format of the knowledge base and rules can be found on the basic syntax.