read →

Collective decision

   read →

Cellular automata

   read →

Emergence

   read →

Swarm Intelligence

   read →

Genetic Algorithms & Evolution

   read →

Kin selection

   read →

Social signalling

(other soon available)

    C++ ants 1
    C++ ants 2
    Fish schools (in French)
The evolution of trust

➜ (2)    Moreover, you are expected to make a team contribution during the week. Please form 4-student teams. The 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 are free to choose any topic that you regard as relevant. If you lack imagination, you may choose one of the topics indicated as "Suggestions for further work" in the above sessions. You may also ask the lecturers.
• Your study should be based on simulation results.
• Your work should include a non-trivial claim, but be realistic about what you can do.
• 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 why).

Your contribution should 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. Do it before Wednesday evening. All members of the team should enter the same title.
If you change your mind, redo the inscription.
    ➜    You may consult other students’ projects. Try to play a minority game!

• You may choose to work together (one to three students per group). In this case, all partners should enter the same project (title, description) on the site.
  All members in the group will 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.

• 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.

• 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)

• Be interesting
• Be scientifically sound    

➜ (4) You will answer a small quiz in English (~ 25 min.)

   read →

QUIZ 2025: Correction

1. Write you report    ➜    Please use this template: MSWord or LibreOffice or LaTeX or Pdf
2. Upload the report, your program and any relevant material    ➜    Uploading page
   The code and the written description might be uploaded until the next Tuesday after the Athens week (in the evening).

• Pierre-Alexandre Murena’s slides on Evolutionary Game Theory.
• Complexity uses in various fields (by Sorin Solomon)
• Genetic Algorithms (JL Dessalles)
• Emergence - Examples and definition (JL Dessalles)
• Emergence of Communication by Pr.Takashi Hashimoto
• Swarm Intelligence (JL Dessalles)
• Morphogenesis
• Small worlds (Pierre Senellart)
• Structure and models of real-world graphs and networks (Jure Leskovec)

• 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.

• Helbig, R. (2016). Four misconceptions about evolution. K!nea Media.
• Complex systems on YouTube
• Bibliography on evolutionary computation