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Enseignement ATHENS - TP09 : Social Emergence in Complex Systems (Télécom Paris - Palaiseau)

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Descriptif

Prerequisites:

All lectures and all materials are in English, so we expect students to be fluent in English. Lab work sessions are based on software written in Python. Mastery of the Python language is not required, but students who attend this course will be fluent in procedural object-oriented programming (Java, C++, Python or equivalent). They will get some knowledge of Python by themselves before the Athens week.  

Objectives

 

The existence of complex social organization is often a mystery. What would bring individuals (people, social insects, birds, artificial agents...) to favor collective benefit rather than short-term selfish payoff? This is the "hard problem" of sociality: the return on investment in the collective is divided by the size of the group, while selfish gains are retained in full.

The emergence of sociality is crucial, not only to understand animal and human societies, but also to gain a new insight into many aspects of the digital life (social media, open-source software communities, Internet technical forums, cooperation among artificial agents, human-computer verbal interaction, acceptability of AI).

This course will explore the conditions for stable social behavior. You will be using computer simulations to study various phenomena (cooperation, coordination, sharing, collective problem solving, communication, charity). You will manipulate several theoretical models (including kin selection, reciprocity and social signaling) that are used to explain these phenomena.

Content

The course will cover several social phenomena, including: collective decision, the cocktail party effect, scale-free social networks, the hawk-dove dilemma, cooperation in insect societies, emergence of segregationism, altruism, the "tragedy of the commons", the "green-beard" effect, social coordination, suicide "for the group", honest communication, charity and competitive helping.

Several theoretical models will be studied, including preferential attachment, kin selection, the Prisoner’s dilemma, the handicap principle, social signaling. Several of these models derive from applying Game Theory to social dilemma.

Computer simulations will include genetic algorithms to simulate natural evolution, and various basic multi-agent techniques to study collective behavior.

Audience

If you are curious about social phenomena and think that theoretical modeling and computer simulation are powerful tools to approach them, then you will enjoy the course.

Prerequisites

All lectures and all materials are in English, so we expect students to be fluent in English. Lab work sessions are based on software written in Python. Mastery of the Python language is not required, but students who attend this course will be fluent in some procedural object-oriented programming language (Java, C++, Python or equivalent). They will get some knowledge of Python by themselves before the Athens week.

Validation

The course consists in lectures alternately with practical work on machines. Students are asked to work on the software platform used to study social phenomena and to perform slight modifications in one of the case studies to develop their own personal (micro )project.

Students will be evaluated based on the following tasks:

  • Answers during Lab work sessions
  • Small open question quiz
  • A 5 min. presentation of their personal project
  • A short written description of their personal project (+ source files)

Lecturers

Main lecturer: Jean-Louis Dessalles - Associate professor at Telecom-Paris (jean-louis.dessalles@telecom-paris.fr )

Other lecturer: Julien Lie-Panis - final year PhD student at Telecom-Paris and Institut Jean Nicod

 

Categories:

Computer science, mathematics (game theory), theoretical sociology, theoretical biology.

30 heures en présentiel

effectifs minimal / maximal:

10/30

Diplôme(s) concerné(s)

Parcours de rattachement

Pour les étudiants du diplôme Diplôme d'ingénieur

All lectures and all materials are in English, so we expect students to be fluent in English. Lab work sessions are based on software written in Python. Mastery of the Python language is not required, but students who attend this course will be fluent in procedural object-oriented programming (Java, C++, Python or equivalent). They will get some knowledge of Python by themselves before the Athens week.  

Format des notes

Numérique sur 20

Littérale/grade réduit

Pour les étudiants du diplôme Data & Artificial Intelligence

L'UE est acquise si Note finale >= 10
  • Crédits ECTS acquis : 3 ECTS

Pour les étudiants du diplôme Diplôme d'ingénieur

L'UE est acquise si Note finale >= 10
  • Crédits ECTS acquis : 3 ECTS
  • Crédit d'UE électives acquis : 3

La note obtenue rentre dans le calcul de votre GPA.

Pour les étudiants du diplôme Echange international non diplomant

L'UE est acquise si Note finale >= 10
  • Crédits ECTS acquis : 3 ECTS

La note obtenue rentre dans le calcul de votre GPA.

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