This introductory textbook provides detailed coverage of the rapidly growing field of complexity science and accommodates readers from a wide variety of backgrounds, and with varying levels of mathematical skill. The book contains a broad range of end of chapter problems and extended projects, with solutions available to instructors online.
This introductory textbook provides detailed coverage of the rapidly growing field of complexity science and accommodates readers from a wide variety of backgrounds, and with varying levels of mathematical skill. The book contains a broad range of end of chapter problems and extended projects, with solutions available to instructors online.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Henrik Jeldtoft Jensen is Professor of Mathematical Physics at Imperial College London, and leads the Centre for Complexity Science. He is a prominent expert in complexity science and is involved in a variety of high-profile research projects including the application of co-evolutionary dynamics to the modelling of socio-economical sustainability, finance, cultural evolution, innovation, and cell diversity in cancer tumour growth, and has also worked with the Guildhall School of Music and Drama to identify differences in the neuronal response of audience and performers depending on the mode of performance. He has published two books on self-organized criticality and complex systems.
Inhaltsangabe
Part I. Conceptual Foundation of Complexity Science: 1. The Science of Emergence 2. Conceptual Framework of Emergence 3. Specific Types of Emergent Behaviour 4. The Value of Prototypical Models of Emergence Part II. Mathematical Tools of Complexity Science: 5. Branching Processes 6. Statistical Mechanics 7. Synchronisation 8. Network Theory 9. Information Theory and Entropy 10. Stochastic Dynamics and Equations for the Probabilities 11. Agent-Based Modelling 12. Intermittency 13. Tipping Points, Transitions and Forecasting 14. Concluding Comments and a Look to the Future.
Part I. Conceptual Foundation of Complexity Science: 1. The Science of Emergence 2. Conceptual Framework of Emergence 3. Specific Types of Emergent Behaviour 4. The Value of Prototypical Models of Emergence Part II. Mathematical Tools of Complexity Science: 5. Branching Processes 6. Statistical Mechanics 7. Synchronisation 8. Network Theory 9. Information Theory and Entropy 10. Stochastic Dynamics and Equations for the Probabilities 11. Agent-Based Modelling 12. Intermittency 13. Tipping Points, Transitions and Forecasting 14. Concluding Comments and a Look to the Future.
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