Acquiring knowledge from expert agents in a structured argumentation setting

Information-seeking interactions in multi-agent systems are required for situations in which there exists an expert agent that has vast knowledge about some topic, and there are other agents (questioners or clients) that lack and need information regarding that topic. In this work, we propose...

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Main Authors: Ramiro Andres Agis, Sebastian Gottifredi, Alejandro Javier García
Format: Article
Language:English
Published: IOS Press 2019-09-01
Series:Argument & Computation
Online Access:https://doi.org/10.3233/AAC-190447
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author Ramiro Andres Agis
Sebastian Gottifredi
Alejandro Javier García
author_facet Ramiro Andres Agis
Sebastian Gottifredi
Alejandro Javier García
author_sort Ramiro Andres Agis
collection DOAJ
description Information-seeking interactions in multi-agent systems are required for situations in which there exists an expert agent that has vast knowledge about some topic, and there are other agents (questioners or clients) that lack and need information regarding that topic. In this work, we propose a strategy for automatic knowledge acquisition in an information-seeking setting in which agents use a structured argumentation formalism for knowledge representation and reasoning. In our approach, the client conceives the other agent as an expert in a particular domain and is committed to believe in the expert’s qualified opinion about a given query. The client’s goal is to ask questions and acquire knowledge until it is able to conclude the same as the expert about the initial query. On the other hand, the expert’s goal is to provide just the necessary information to help the client understand its opinion. Since the client could have previous knowledge in conflict with the information acquired from the expert agent, and given that its goal is to accept the expert’s position, the client may need to adapt its previous knowledge. The operational semantics for the client-expert interaction will be defined in terms of a transition system. This semantics will be used to formally prove that, once the client-expert interaction finishes, the client will have the same assessment the expert has about the performed query.
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spelling doaj.art-6e9864b3b4434c2a837fd668f3a8eb2f2023-03-24T09:48:02ZengIOS PressArgument & Computation1946-21661946-21742019-09-0110214918910.3233/AAC-190447Acquiring knowledge from expert agents in a structured argumentation settingRamiro Andres Agis0Sebastian Gottifredi1Alejandro Javier García2Institute for Computer Science and Engineering (UNS-CONICET), Department of Computer Science and Engineering, Universidad Nacional del Sur, Bahía Blanca, Argentina. E-mails: ramiro.agis@cs.uns.edu.ar, sg@cs.uns.edu.ar, ajg@cs.uns.edu.arInstitute for Computer Science and Engineering (UNS-CONICET), Department of Computer Science and Engineering, Universidad Nacional del Sur, Bahía Blanca, Argentina. E-mails: ramiro.agis@cs.uns.edu.ar, sg@cs.uns.edu.ar, ajg@cs.uns.edu.arInstitute for Computer Science and Engineering (UNS-CONICET), Department of Computer Science and Engineering, Universidad Nacional del Sur, Bahía Blanca, Argentina. E-mails: ramiro.agis@cs.uns.edu.ar, sg@cs.uns.edu.ar, ajg@cs.uns.edu.ar Information-seeking interactions in multi-agent systems are required for situations in which there exists an expert agent that has vast knowledge about some topic, and there are other agents (questioners or clients) that lack and need information regarding that topic. In this work, we propose a strategy for automatic knowledge acquisition in an information-seeking setting in which agents use a structured argumentation formalism for knowledge representation and reasoning. In our approach, the client conceives the other agent as an expert in a particular domain and is committed to believe in the expert’s qualified opinion about a given query. The client’s goal is to ask questions and acquire knowledge until it is able to conclude the same as the expert about the initial query. On the other hand, the expert’s goal is to provide just the necessary information to help the client understand its opinion. Since the client could have previous knowledge in conflict with the information acquired from the expert agent, and given that its goal is to accept the expert’s position, the client may need to adapt its previous knowledge. The operational semantics for the client-expert interaction will be defined in terms of a transition system. This semantics will be used to formally prove that, once the client-expert interaction finishes, the client will have the same assessment the expert has about the performed query.https://doi.org/10.3233/AAC-190447
spellingShingle Ramiro Andres Agis
Sebastian Gottifredi
Alejandro Javier García
Acquiring knowledge from expert agents in a structured argumentation setting
Argument & Computation
title Acquiring knowledge from expert agents in a structured argumentation setting
title_full Acquiring knowledge from expert agents in a structured argumentation setting
title_fullStr Acquiring knowledge from expert agents in a structured argumentation setting
title_full_unstemmed Acquiring knowledge from expert agents in a structured argumentation setting
title_short Acquiring knowledge from expert agents in a structured argumentation setting
title_sort acquiring knowledge from expert agents in a structured argumentation setting
url https://doi.org/10.3233/AAC-190447
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