Cantu, Francisco JCeballos Cansino, Héctor Gibrán2019-12-182019-12-182009-11-13978-076953933-1http://hdl.handle.net/11285/636097In 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.enghttp://creativecommons.org/licenses/by-nc-nd/4.0/ScienceArtículo de conferencia8th Mexican International Conference on Artificial Intelligence - Proceedings of the Special Session, MICAI 2009Intelligent agents6772México / Mexico