Corporate with Aobo on one paper, maybe two, for the Special Issue “Causality and Complex Systems”.
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Got the email from Prof.Zhang, the Special Issue Editors as follows.
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Dear Colleague:
We contact you because we are organizing a Special Issue entitled “Causality and Complex Systems”, to be published in the journal of Entropy (IF(2021): 2.738), the deadline for manuscript submissions: 25 April 2023
Complex Systems, e.g., living systems, environmental systems, health and medical systems, socioeconomic systems, and even online communities are all unified wholes that are formed by a large number of interacting units. One of the reasons for the system complexity is the wide existence of entangled causal structures. The causality may be emergent, which means stronger causal laws may exist at the macro-scale rather than the micro-scale (e.g., statistical mechanics). The causal force also may cross different levels. For example, downward causality, meaning the collective behaviors or the aggregated variables of the whole system (e.g., price) may have an effect on individual behaviors that widely exist in living systems or social systems. Therefore, understanding the emergence and evolution of these causal structures on various scales within a large complex system is very important.
However, how to discover intricate causal relationships and identify emerging causal laws on a macro level from the behavioral data of complex systems, and how to use these causal relationships and laws to infer new information are all tough problems. New emergent machine learning technologies (e.g., causal representation learning, causal reinforcement learning); information theory (e.g., information decomposition); causal discovery; causal inference, and so forth will offer us new solutions. This Special Issue focuses on, but is not limited to, the following topics: Causal discovery; Causal inference; Causal emergence; Downward causality; Measures of complexity and causality; Complex system modeling; Causal machine learning; Causal representation learning; Causal reinforcement learning; Information decomposition; Related applications. Prof. Dr. Jiang Zhang Dr. Peng Cui Guest Editors
Based on your expertise in this field, we think you could make an excellent contribution. For further reading, please follow the link to the Special Issue Website at:
https://www.mdpi.com/journal/entropy/special_issues/causality_complex_systems
We look forward to hearing from you.
(If you already provided feedback, please disregard this message.)
– Jiang Zhang
Professor
School of Systems Science, Beijing Normal University, Beijing, China, 100875
My website: http://www.swarma.org/jake