@inbook{f9a624d0a74549adbc29aeb6f4d871a7,
title = "Choosing appropriate arguments from trustworthy sources",
abstract = "Recently, argumentation frameworks have been extended in order to consider trust when defining preferences between arguments, given that arguments (or information that supports the arguments) from more trustworthy sources may be preferred to arguments from less trustworthy sources. Although such literature presents interesting results on argumentation-based reasoning and how agents define preferences between arguments, there is little work taking into account agent strategies for argumentation-based dialogues using such information. In this work, we propose an argumentation framework in which agents consider how much the recipient of an argument trusts others in order to choose the most suitable argument for that particular recipient, i.e., arguments constructed using information from those sources that the recipient trusts. Our approach aims to allow agents to construct more effective arguments, depending on the recipients and on their views on the trustworthiness of potential sources.",
keywords = "Argumentation, Multi-Agent Systems, Reputation, Trust",
author = "Panisson, {Alison R.} and Simon Parsons and Peter McBurney and Bordini, {Rafael H.}",
year = "2018",
month = jan,
day = "1",
doi = "10.3233/978-1-61499-906-5-345",
language = "English",
isbn = "9781614999058",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press",
pages = "345--352",
booktitle = "Computational Models of Argument - Proceedings of COMMA 2018",
note = "7th International Conference on Computational Models of Argument, COMMA 2018 ; Conference date: 12-09-2018 Through 14-09-2018",
}