Publication type: Pedagogic
Author: Rui A. Pita Perdigão (R.A.P. Perdigão)
Title: Complex System Dynamics
Methodological Keywords: Complex Systems, Dynamical Systems, Information Theory, Mathematical Physics, Information Physics, Non-Ergodic, Chaos, Entropy, Emergence, Synergy, Coevolution.
Applied Keywords: Big Data Analytics, Artificial Intelligence, Machine Learning, Earth System Dynamics, Socio-Environmental Systems, Climate Change, Sustainability.
Rui Perdigão’s doctoral course on Complex System Dynamics is headquartered and primarily delivered at the Meteoceanics Institute for Complex System Science. Moreover, since 2019 it is also available as a semester doctoral course at the University of Lisbon (offering 6 ECTS for students enrolled in partner programs). The course is specially tailored to a wide-spectrum interdisciplinary audience spanning across natural, social, technical and exact sciences.
The associated pedagogic materials emerge as a natural guide for graduate students, researchers and practitioners alike, matching the structure of the course as follows:
- Acquisition of fundamental competences in complexity sciences, their relevance and implementation in the conceptualization, systematization, modeling and formal analysis of the complex dynamics underlying climate change;
- Learning fundamental principles that allow to formulate the dynamics of complex systems, including emergence of extreme phenomena, in an elegantly simple and effective way without loss of rigor nor generality;
- Deepening scientific research, development and communication at the interface between natural and social frontier sciences.
- Fundamental notions on the dynamics of complex systems, principles and underlying mechanisms in dynamic systems theory and physical information;
- Methods of systematization of dynamic systems: simple conceptual structures representing complex natural, technical and social phenomena;
- Fundamentals of the dynamics of the Earth system and the emergence of regimes, critical transitions and extreme events in the context of complexity sciences;
- Coevolutionary models of climate change in a holistic perspective involving dynamics of the oceans, atmosphere, geosphere, biosphere and society;
- Dynamic methods of extraction and analysis of information related to the dynamics of complex systems, from empirical and computational records;
- Detection of patterns of spatial and temporal climatic variability from data of the dynamics of the Earth system and attribution to underlying mechanisms;
- Methods of evaluating uncertainty and predictability in complex system dynamics, for representative model optimization and decision support.
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