Complex Systems Summer School 2016-Panel Questions
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Revision as of 17:37, 23 June 2016 by Juster
Please post questions you might have for our panel. Panel includes Simon DeDeo, Josh Grochow, Elly Power, Jessica Flack
- Compared with machine learning or data mining, we may feel that complex systems have less practical applications in enterprise development. How to better adopt the theories and profits of complexity into practical production and make this field better as a demand-driven research, as well as research guided production?
- Systems like social activities and economic activities are quite complex. The trends of agent-based modelling usually simplifies or ignores many mechanisms and conditions, which are far away from real situations. Can we use these "toy models" to solve real world financial crisis, fight against terrorist organizations or protect civil rights?
- How do you distinguish between research you'd consider to be complexity science or not?
- Is it true that doing interdisciplinary research makes it harder to find an academic position? What advice do you have looking for academic jobs when you sit between disciplines (besides, of course, getting a position at SFI).
- A paraphrasis of an Einstein's quote was used in one of our lectures: “Make things as simple as possible, but not simpler.” When is a toy model too simple? When is a data analysis too simple?
- Complexity science has roots in the physics. In applying its tools and methods in social science, what kinds of change of perspectives are needed? Can you show some examples?
- Echoing to the previous question, I argue that complexity paradigms were simultaneously discovered and used in the social sciences (e.g. in theoretical and quantitative geography)