Publications from our Researchers

Several of our current PhD candidates and fellow researchers at the Data Science Institute have published, or in the proccess of publishing, papers to present their research.  

Citation

BibTex format

@article{Mediano:2022:10.1098/rsta.2021.0246,
author = {Mediano, PAM and Rosas, FE and Luppi, AI and Jensen, HJ and Seth, AK and Barrett, AB and Carhart-Harris, RL and Bor, D},
doi = {10.1098/rsta.2021.0246},
journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences},
pages = {20210246--20210246},
title = {Greater than the parts: a review of the information decomposition approach to causal emergence.},
url = {http://dx.doi.org/10.1098/rsta.2021.0246},
volume = {380},
year = {2022}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Emergence is a profound subject that straddles many scientific disciplines, including the formation of galaxies and how consciousness arises from the collective activity of neurons. Despite the broad interest that exists on this concept, the study of emergence has suffered from a lack of formalisms that could be used to guide discussions and advance theories. Here, we summarize, elaborate on, and extend a recent formal theory of causal emergence based on information decomposition, which is quantifiable and amenable to empirical testing. This theory relates emergence with information about a system's temporal evolution that cannot be obtained from the parts of the system separately. This article provides an accessible but rigorous introduction to the framework, discussing the merits of the approach in various scenarios of interest. We also discuss several interpretation issues and potential misunderstandings, while highlighting the distinctive benefits of this formalism. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.
AU  - Mediano,PAM
AU  - Rosas,FE
AU  - Luppi,AI
AU  - Jensen,HJ
AU  - Seth,AK
AU  - Barrett,AB
AU  - Carhart-Harris,RL
AU  - Bor,D
DO  - 10.1098/rsta.2021.0246
EP  - 20210246
PY  - 2022///
SN  - 1364-503X
SP  - 20210246
TI  - Greater than the parts: a review of the information decomposition approach to causal emergence.
T2  - Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
UR  - http://dx.doi.org/10.1098/rsta.2021.0246
UR  - https://www.ncbi.nlm.nih.gov/pubmed/35599558
UR  - https://royalsocietypublishing.org/doi/10.1098/rsta.2021.0246
UR  - http://hdl.handle.net/10044/1/97537
VL  - 380
ER  -
Download

Contact us

Data Science Institute

William Penney Laboratory
Imperial College London
South Kensington Campus
London SW7 2AZ
United Kingdom

Email us.

Sign up to our mailing list.

Follow us on Twitter, LinkedIn and Instagram. 


Download now

DSI Annual Report 2022
Cover of Data Science Institute booklet

Download now

Data Science Institute Find out more about the Institute