Complexity A Guided Tour
Abstract
As science probes the nature of life, society, and technology ever more closely, what it finds there is complexity. The sophisticated group behavior of social insects, the unexpected intricacies of the genome, the dynamics of population growth, and the self-organized structure of the World Wide Web - these are just a few examples of complex systems that still elude scientific understanding. Comprehending such systems seems to require a wholly new approach, one that goes beyond traditional scientific reductionism and that re-maps long-standing disciplinary boundaries. This remarkably accessible and companionable book, written by a leading complex systems scientist, provides an intimate, detailed tour of the sciences of complexity, a broad set of efforts that seek to explain how large-scale complex, organized, and adaptive behavior can emerge from simple interactions among myriad individuals. In this richly illustrated work, Melanie Mitchell describes in equal parts the history of ideas underlying complex systems science, the current research at the forefront of this field, and the prospects for the field's contribution to solving some of the most important scientific questions of our current century.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
There is no common understanding of the basic paradigmatic assumptions of complexity theory, even among complexity scientists themselves, including the matter of defining complexity.
“On the other hand, there is no common understanding of the basic paradigmatic assumptions of complexity theory, even among the complexity scientists themselves-including the matter of defining complexity (Mitchell, 2009).”
From Complexity and Organizational Communication: A Quest for Common Ground (2016) · cites this paper as Mitchell, 2009
Cited by
Sorted by citations
Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems
Grieves, M., & Vickers, J. (2017) · Transdisciplinary Perspectives on Complex Systems · doi:10.1007/978-3-319-38756-7_4 · Cited by 3,727 · see citing works
Moore, G. F., Evans, R. E., Hawkins, J., Littlecott, H., Melendez-Torres, G. J., Bonell, C., & Murphy, S. (2019) · Evaluation · doi:10.1177/1356389018803219 · Cited by 471 · see citing works
Acoustic sequences in non‐human animals: a tutorial review and prospectus
Kershenbaum, A., Blumstein, D. T., Roch, M. A., Akçay, Ç., Backus, G., Bee, M. A., Bohn, K., Cao, Y., Carter, G., Cäsar, C., et al. (2016) · Biological Reviews · doi:10.1111/brv.12160 · Cited by 337 · see citing works
Synchronous failure: the emerging causal architecture of global crisis
Homer-Dixon, T., Walker, B., Biggs, R., Crépin, A.-S., Folke, C., Lambin, E. F., Peterson, G. D., Rockström, J., Scheffer, M., Steffen, W., et al. (2015) · Ecology and Society · doi:10.5751/es-07681-200306 · Cited by 244 · see citing works
The emergence of global systemic risk
Centeno, M. A., Nag, M., Patterson, T. S., Shaver, A., & Windawi, A. J. (2015) · Annual Review of Sociology · doi:10.1146/annurev-soc-073014-112317 · Cited by 240 · see citing works
Security and Privacy Issues in Intelligent Transportation Systems: Classification and Challenges
Hahn, D., Munir, A., & Behzadan, V. (2021) · IEEE Intelligent Transportation Systems Magazine · doi:10.1109/mits.2019.2898973 · Cited by 183 · see citing works
The evolutionary ecology of technological innovations
Solée, R. V., Valverde, S., Casals, M. R., Kauffman, S. A., Farmer, D., & Eldredge, N. (2013) · Complexity · doi:10.1002/cplx.21436 · Cited by 140 · see citing works
Farming Systems Research: an approach to inquiry
Darnhofer, I., Gibbon, D., & Dedieu, B. (2012) · Farming Systems Research into the 21st Century: The New Dynamic · doi:10.1007/978-94-007-4503-2_1 · Cited by 129 · see citing works
Measuring the complexity of the law: the United States Code
Katz, D. M., & Bommarito, M. J. (2014) · Artificial Intelligence and Law · doi:10.1007/s10506-014-9160-8 · Cited by 117 · see citing works
Conceptualizing Emergent States: A Strategy to Advance the Study of Group Dynamics
Waller, M. J., Okhuysen, G. A., & Saghafian, M. (2016) · Academy of Management Annals · doi:10.5465/19416520.2016.1120958 · Cited by 143 · see citing works
Chandler, J., Rycroft‐Malone, J., Hawkes, C., & Noyes, J. (2016) · Journal of Advanced Nursing · doi:10.1111/jan.12815 · Cited by 70 · see citing works
Gilpin, D. R., & Miller, N. K. (2013) · Communication Theory · doi:10.1111/comt.12008 · Cited by 25 · see citing works
How to Solve Problems with Crowds: A Computer‐Based Simulation Model
Vuculescu, O., & Bergenholtz, C. (2014) · Creativity and Innovation Management · doi:10.1111/caim.12059 · Cited by 22 · see citing works
The Free Energy Principle: Good Science and Questionable Philosophy in a Grand Unifying Theory
Sánchez-Cañizares, J. (2021) · Entropy · doi:10.3390/e23020238 · Cited by 16 · see citing works
Complexity and Organizational Communication: A Quest for Common Ground
Poutanen, P., Siira, K., & Aula, P. (2016) · Human Resource Development Review · doi:10.1177/1534484316639713 · Cited by 10 · see citing works
Sources of Opacity in Computer Systems: Towards a Comprehensive Taxonomy
Mann, S., Crook, B., Kästner, L., Schomäcker, A., & Speith, T. (2023) · 2023 IEEE 31st International Requirements Engineering Conference Workshops (REW) · doi:10.1109/rew57809.2023.00063 · Cited by 10 · see citing works
Information Measures of Complexity, Emergence, Self-organization, Homeostasis, and Autopoiesis
Fernandez, N., Maldonado, C., & Gershenson, C. (2013) · arXiv · doi:10.48550/arxiv.1304.1842 · Cited by 1 · see citing works
Outlining Traceability: A Principle for Operationalizing Accountability in Computing Systems
Kroll, J. A. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3442188.3445937 · Cited by 2 · see citing works
- Authors
- Mitchell, M.
- Corresponding author
- Mitchell, Melanie
- ORCID
- Mitchell, Melanie
- Publisher
- Oxford University PressNew York, NY
- Published
- 2009-04-01
- OpenAlex
- W1787929695
- Cited by
- 2,310
- References
- 0
- Citations by year
- 2026: 184 · 2025: 153 · 2024: 152 · 2023: 156 · 2022: 167 · 2021: 210 · 2020: 176 · 2019: 196 · 2018: 131 · 2017: 126 · 2016: 123 · 2015: 142 · 2014: 115 · 2013: 83 · 2012: 95
- FWCI
- 21.33
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
- Oxford University Press eBooks
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Systems and Dynamics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Chaos, Complexity, and Education
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
- Keywords
- complex systems, emergence, self-organization, adaptive behavior, reductionism, social insects, genome complexity, population dynamics, World Wide Web, interdisciplinary research
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
