Algorithmic independence of initial condition and dynamical law in thermodynamics and causal inference

dc.contributor.authorJanzing, Dominik
dc.contributor.authorAraújo, Rafael Chaves Souto
dc.contributor.authorSchölkopf, Berhnard
dc.date.accessioned2020-10-13T17:58:14Z
dc.date.available2020-10-13T17:58:14Z
dc.date.issued2016-09-27
dc.description.resumoWepostulate a principle stating that the initial condition of a physical system is typically algorithmically independent of the dynamical law.Wediscuss the implications of this principle and argue that they link thermodynamics and causal inference. On the one hand, they entail behavior that is similar to the usual arrow of time. Onthe other hand, they motivate a statistical asymmetry between cause and effect that has recently been postulated in the field of causal inference, namely, that the probability distribution Pcause contains no information about the conditional distribution Peffect cause and vice versa, while Peffect may contain information about Pcause effectpt_BR
dc.identifier.citationJANZING, Dominik; CHAVES, Rafael; SCHÖLKOPF, Bernhard. Algorithmic independence of initial condition and dynamical law in thermodynamics and causal inference. New Journal of Physics, [S.L.], v. 18, n. 9, p. 093052, 27 set. 2016. Disponível em: https://iopscience.iop.org/article/10.1088/1367-2630/18/9/093052. Acesso em: 01 out. 2020. http://dx.doi.org/10.1088/1367-2630/18/9/093052.pt_BR
dc.identifier.doi10.1088/1367-2630/18/9/093052.
dc.identifier.issn1367-2630
dc.identifier.urihttps://repositorio.ufrn.br/handle/123456789/30398
dc.languageenpt_BR
dc.publisherIOP Publishingpt_BR
dc.rightsAttribution 3.0 Brazil*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/br/*
dc.subjectArrow of timept_BR
dc.subjectCausal inferencept_BR
dc.subjectKolmogorov complexitypt_BR
dc.subjectPhysical entropypt_BR
dc.subjectAlgorithmic randomnesspt_BR
dc.titleAlgorithmic independence of initial condition and dynamical law in thermodynamics and causal inferencept_BR
dc.typearticlept_BR

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