Telecom Paris Dep. Informatique & Réseaux J-L. Dessalles ← Home page December 2024

Module Athens TP-09

    Emergence in Complex Systems

Lecturers:

Ada Diaconescu - Associate professor at Telecom-Paris

Jean-Louis Dessalles - Associate professor at Telecom-Paris

Samuel Reyd - PhD student at Telecom-Paris

                            ➜    other AI courses

    

➜    [Presentation] 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.             

• First contact with Evolife (← recommended to be read first)
• Emerging Phenomena
• Emerging Behaviour
• Emerging sociality
• Behavioural Ecology
• Emergence of communication

    Don’t panic! You are not expected to be exhaustive.

    
➜    [Docs, Biblio & Links] (below)

click to display ➜

read →     Collective decision        read →     Cellular automata     See also these nice slides by Leigh Tesfatsion and these ones by Nicolas Ollinger    read →     Emergence        read →     Small worlds        read →     Swarm Intelligence

read →     Genetic Algorithms & Evolution        read →     Altruism        read →     Kin selection        read →     Cooperation 1

read →     Cooperation 2        read →     Signalling 1        read →     Signalling 2

    C++ ants 1
    C++ ants 2
    Fish schools (in French)
The evolution of trust ➜ (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 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.
• 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 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. Do it before Wednesday evening. If you change your mind, redo the inscription.
    ➜    You may consult other students’ projects. Try to play a minority game in your choice!

• 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.
• 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 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 answer a small quiz in English (~ 25 min.)

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