A curated list of resources for studying complex systems science, covering concepts, models, software, and communities.
Awesome Complexity is a curated, comprehensive directory of resources dedicated to the interdisciplinary field of complex systems science. It aggregates high-quality links to scientific journals, blogs, societies, organizations, computational models, software tools, and educational materials. The project serves as a central hub for discovering key concepts, tools, and literature for understanding systems with emergent properties and non-linear interactions.
This resource is designed for researchers, students, and enthusiasts entering or working within the field of complex systems science who need a structured, vetted starting point for literature, models, and software. It is particularly valuable for individuals in interdisciplinary fields like computational biology, network science, or agent-based modeling seeking foundational knowledge and tools.
Developers and researchers choose Awesome Complexity over general searches because it provides a community-vetted, well-organized, and comprehensive aggregation specifically for complexity science, lowering the barrier to entry. Its unique value lies in combining a glossary of core concepts with practical directories for models and software, all curated under the principle of open knowledge sharing.
An awesome list of complex systems science resources
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Aggregates high-quality links to journals, blogs, societies, and tools in one organized place, as evidenced by sections like 'Scientific Journals' and 'Software' with specific entries.
Provides clear definitions and Wikipedia links for foundational ideas like emergence and chaos, making it easy for newcomers to grasp key terminology without prior knowledge.
Details classic computational models such as Cellular Automata and Boids, with links to implementations and resources like Golly for Game of Life, aiding in practical application and experimentation.
Includes references to books, online courses, and interactive websites like Complexity Explorer, supporting self-directed learning in complex systems science from various angles.
The software directory lists tools like NetLogo and Repast but lacks in-depth comparisons, installation guides, or usage examples, requiring additional research for practical use.
As a curated GitHub list, it may not be frequently updated, leading to stale links or missing recent developments in this fast-evolving field, as seen with limited journal entries.
The README is a static markdown file without built-in search or filtering functionality, making it cumbersome to navigate for specific needs among hundreds of links.