CEU Electronic Theses and Dissertations, 2025
| Author | Hanics, Mihaly |
|---|---|
| Title | Combinatorial Interpretations Of Frameworks Of Emergence Offer Novel Ways To Study Synergy, Self-Organization And Redundancy |
| Summary | The study of complex systems, such as the human brain, the weather, or societies have been core scientific challenges in their respective fields. Despite their incomprehensible nature, these share similarities and prompted researchers to establish the field of complexity science, which studies complex systems systematically, aiming to provide general tools for complex system analysis. The most prominent feature of complex systems is the presence of emergent phenomena. Emergence has been a highly debated concept of science and philosophy, it refers to patterns that arise via interactions in a system, that do not exist on the level of individual entities. It is related to the gestalt psychology, the notion of "systems equalling more than sum of their parts", Mark Bedau’s "weak emergence" concept and so on. Emergent features are generally believed to be not deducible from the rules of entities alone, the interactions and the initial states also matter and are necessary for derivation. There have been various mathematical frameworks of emergence, most of which are statistical, with the 2-3 major approaches using tools of information theory. In this thesis, I attempt to reform the field by taking a combinatorial approach, breaking with the statistical approach in theory, and define the new "dynamics-unfolding measure for connecting various concepts of these frameworks and complexity science. This approach can help us better understand complex systems, and mathematically derive dynamical patterns |
| Supervisor | Battiston, Federico |
| Department | Network Science MSc |
| Full text | https://www.etd.ceu.edu/2025/hanics_mihaly.pdf |
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