Introduction to Complexity

Melanie Mitchell
Level: beginner
University: Santa Fe Institute
Platform: Complexity Explorer
Recurrence: always
Language: English
Discipline: Economics
Attendance: free
Workload per week: 4.5 h

In a span of around 12 weeks, the course covers a wide range of topics including agent-based modeling, networks, dynamic, chaos, information, fractals, cooperation models and scaling in biology and society. The course acts as a perfect beginner level introduction spanning a wide range of topics in the field of complexity.

Despite the course being introductory in nature, it covers a wide range of complexity related topics that would be of value even to more experienced learners. The course explores topics such as agent-based modeling, networks, dynamic, chaos, information, fractals, cooperation models and scaling in biology and society with an emphasis on hands-on problem-solving exercises through the modeling software, NetLogo, thus giving learners a chance to apply theory to practice. At the end of the course, one can expect to gain a taste of the tools used by complexity scientists in explaining complexity in nature, society, and technology. There are no mathematics or science background prerequisites for the course.

Comment from our editors:

It is an important and broad overview of complexity. While it isn’t specifically for Complexity economics it covers important tools used in complexity economics and has examples from behavioral economics and social science. Moreover, it gives a good introduction to basic programming skills.

Subtitles and transcripts available in Spanish, French, Portuguese, Brazilian

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Nous soutenir

Ce projet est le fruit du travail des membres du réseau international pour le pluralisme en économie, dans la sphère germanophone (Netzwerk Plurale Ökonomik e.V.) et dans la sphère francophone (Rethinking Economics Switzerland / Rethinking Economics Belgium / PEPS-Économie France). Nous sommes fortement attachés à notre indépendance et à notre diversité et vos dons permettent de le rester ! 

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