| dc.contributor.author | Ay, N. | |
| dc.contributor.author | Polani, D. | |
| dc.date.accessioned | 2013-01-15T12:28:56Z | |
| dc.date.available | 2013-01-15T12:28:56Z | |
| dc.date.issued | 2008 | |
| dc.identifier.citation | Ay , N & Polani , D 2008 , ' Information flows in causal networks ' , Advances in Complex Systems , vol. 11 , no. 1 , pp. 17-41 . https://doi.org/10.1142/S0219525908001465 | |
| dc.identifier.issn | 0219-5259 | |
| dc.identifier.other | dspace: 2299/1965 | |
| dc.identifier.other | ORCID: /0000-0002-3233-5847/work/86098110 | |
| dc.identifier.uri | http://hdl.handle.net/2299/9649 | |
| dc.description.abstract | We use a notion of causal independence based on intervention, which is a fundamental concept of the theory of causal networks, to define a measure for the strength of a causal effect. We call this measure “information flow” and compare it with known information flow measures such as transfer entropy | en |
| dc.format.extent | 291999 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | Advances in Complex Systems | |
| dc.title | Information flows in causal networks | en |
| dc.contributor.institution | Centre for Computer Science and Informatics Research | |
| dc.contributor.institution | Adaptive Systems | |
| dc.contributor.institution | Department of Computer Science | |
| dc.contributor.institution | School of Physics, Engineering & Computer Science | |
| dc.contributor.institution | Centre for Future Societies Research | |
| dc.description.status | Peer reviewed | |
| rioxxterms.versionofrecord | 10.1142/S0219525908001465 | |
| rioxxterms.type | Journal Article/Review | |
| herts.preservation.rarelyaccessed | true | |
