Module Athens TPT-09
Emergence in Complex Systems
From nature to engineering
→ other AI courses
The course is divided in several chapters corresponding to lectures. Each chapter proposes several topics.
Don’t hesitate to skip some of them and go directly to those that match your interests best. Try to work on topics from all these chapters until Wednesday evening.
Don’t panic! You are not expected to be exhaustive.
→ (1) Your answers during the Lab Work sessions will be recorded and evaluated.
→ (2) Moreover, you are expected to make a personal contribution during the week.
This contribution is typically an improvement on some issue studied during the Lab Work sessions. You should pick a problem that you want to investigate further. Initiative is welcome.
- You may choose one of the topics indicated as "Suggestions for further work" in the above sessions, but you are free to choose any topic that you regard as relevant.
- Your study should be based on simulation results.
- You should seek for simple and clear-cut results from which we can learn something (even if you study is inconclusive, we want to know clearly why).
Initiative and logical clarity will be appreciated.
- Try to be realistic about what you can do. Your work should not be trivial, but it should lead somewhere.
Your contribution shoud be achieved using the Evolife platform. If it involves code, this code should be in Python.
Please indicate here what you intend to do as a project.
You may decide as soon as Tuesday evening.
If you change your mind, redo the inscription.
→ You may consult the others’ projects. Try to play a minority game in your choice!
You may choose to work in pairs. In this case, both partners should enter the same project (title, description) on the site.
Both members of the pair should be heard during the Friday presentation.
If you opt for a common report, then the report should include two separate parts that make clear who did what.
On Thursday evening :
- Please upload a few slides (from one to three) that illustrate your work (.pdf or .ppt or .pptx; openoffice should also be ok).
Try to be visual, avoid text (bullet lists forbidden!).
DON’T SEND ANYTHING THROUGH EMAIL. Use the upload program.
To capture images from Evolife, use the [Photo] button (or [P] shortcut). To make movies, press [V] to enter the film (or video) mode.
Images are stored in ___Result; you have to assemble them to make a movie. Avoid embedding movies into .pptx, or only as gif images.
- Please upload additional relevant material, such as:
- A python code file, typically a modified Evolife scenario) for the record.
- A short text presenting what you achieved (problem, solution, results, links to references) (and again, don’t send any file through email)
→ (3) You will be ask to talk during 4 minutes about your small study (from you seat).
Your audience is not the teachers, but the other students.
- Be interesting
- Be scientifically sound
→ (4) You will be asked to answer a small quiz in English (~ 20 min.)
- The code and the written description might be uploaded until the next Tuesday after the Athens week (in the evening).
- Amblard, F. & Phan, D. (2007). Agent-based modelling and simulation in the social and human sciences. Oxford: The Bardwell-Press.
- Bonabeau, E., Dorigo, M. & Theraulaz, G. (1999). Swarm intelligence: from natural to artificial systems. Oxford: Oxford University Press.
- Camazine, S., Deneubourg, J.-l., Franks, N. R., Sneyd, J., Theraulaz, G. & Bonabeau, E. (2001). Self-organization in biological systems. Princeton, NJ: Princeton University Press.
- Dessalles, J.-L. (1996). L’ordinateur génétique. Paris: Hermes Science.
- Dessalles, J.-L., Gaucherel, C. & Gouyon, P.-H. (2016). Le fil de la vie - La face immatérielle du vivant. Paris: Odile Jacob.
- Goldberg, D. E. (1989). Genetic algorithms in search, optimization and machine learning. Reading (MA): Addison Wesley Publishing Company.
- Easley, D. & Kleinberg, J. (2010). Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge University Press.
- Goldberg, D. E. (1989). Algorithmes génétiques - Exploration, optimisation et apprentissage automatique. Paris: Addison Wesley France, ed. 1994.
- Hansell, M. (2007). Built by animals. Oxford, UK: Oxford University Press.
- Holland, J. H. (1975). Adaptation in natural and artificial systems. Cambridge, MA: MIT Press, ed. 1992.
- Kauffman, S. (1993). The origins of order: self-organization and selection in evolution. Oxford university press.
- Rennard, J.-P. (2002). Vie artificielle - Où la biologie rencontre l’informatique. Paris: Vuibert.
- Steeb, W.-H. (2008). The nonlinear workbook (5th ed.). Singapore: World Scientific.