Merging plans with incomplete knowledge about actions and goals through an agent-based reputation system

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Bibliographische Detailangaben
Hauptverfasser:	Carbo, Javier, Molina, Jose M, Patricio, Miguel A
Format:	Preprint
Veröffentlicht:	2024
Schlagworte:	Artificial Intelligence
Online-Zugang:	Acceder al recurso
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author	Carbo, Javier Molina, Jose M Patricio, Miguel A
author_facet	Carbo, Javier Molina, Jose M Patricio, Miguel A
contents	Managing transition plans is one of the major problems of people with cognitive disabilities. Therefore, finding an automated way to generate such plans would be a helpful tool for this community. In this paper we have specifically proposed and compared different alternative ways to merge plans formed by sequences of actions of unknown similarities between goals and actions executed by several operator agents which cooperate between them applying such actions over some passive elements (node agents) that require additional executions of another plan after some time of use. Such ignorance of the similarities between plan actions and goals would justify the use of a distributed recommendation system that would provide an useful plan to be applied for a certain goal to a given operator agent, generated from the known results of previous executions of different plans by other operator agents. Here we provide the general framework of execution (agent system), and the different merging algorithms applied to this problem. The proposed agent system would act as an useful cognitive assistant for people with intelectual disabilities such as autism.
format	Preprint
id	arxiv_https___arxiv_org_abs_2402_00064
institution	arXiv
publishDate	2024
record_format	arxiv
spellingShingle	Merging plans with incomplete knowledge about actions and goals through an agent-based reputation system Carbo, Javier Molina, Jose M Patricio, Miguel A Artificial Intelligence Managing transition plans is one of the major problems of people with cognitive disabilities. Therefore, finding an automated way to generate such plans would be a helpful tool for this community. In this paper we have specifically proposed and compared different alternative ways to merge plans formed by sequences of actions of unknown similarities between goals and actions executed by several operator agents which cooperate between them applying such actions over some passive elements (node agents) that require additional executions of another plan after some time of use. Such ignorance of the similarities between plan actions and goals would justify the use of a distributed recommendation system that would provide an useful plan to be applied for a certain goal to a given operator agent, generated from the known results of previous executions of different plans by other operator agents. Here we provide the general framework of execution (agent system), and the different merging algorithms applied to this problem. The proposed agent system would act as an useful cognitive assistant for people with intelectual disabilities such as autism.
title	Merging plans with incomplete knowledge about actions and goals through an agent-based reputation system
topic	Artificial Intelligence
url	https://arxiv.org/abs/2402.00064

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