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dc.contributor.authorCantu, Francisco J
dc.contributor.authorCeballos Cansino, Héctor Gibrán
dc.date.accessioned2019-12-18T16:58:25Z
dc.date.available2019-12-18T16:58:25Z
dc.date.issued2009-11-13
dc.identifier.isbn978-076953933-1
dc.identifier.urihttp://hdl.handle.net/11285/636097
dc.description.abstractIn this paper we present a Causal Artificial Intelligence Design (CAID) theory that borrows notions from Classical philosophy for modeling intelligent agents. Principles introduced by this theory are used for extending a goal-driven BDI architecture and implementing what we call Causal Agent. This architecture incorporates causal formalisms like Pearl's Do calculus and C+ which are adapted to Semantic Web knowledge representations. Our approach includes an ontological agent description that enables and justifies the instantiation of agents as part of a plan. An experimental prototype used for validating experimentally our approach is commented.es_MX
dc.language.isoenges_MX
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subject.lcshSciencees_MX
dc.titleTowards a causal framework for intelligent agents developmentes_MX
dc.typeArtículo de Conferencia / Conference Articlees_MX
dc.identifier.journal8th Mexican International Conference on Artificial Intelligence - Proceedings of the Special Session, MICAI 2009es_MX
dc.subject.keywordIntelligent agentses_MX
dc.identifier.startpage67es_MX
dc.identifier.endpage72es_MX
dc.contributor.affiliationInstituto Tecnológico y de Estudios Superiores de Monterreyes_MX
dc.subject.lembMéxico / Mexicoes_MX


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