Freshmen Discovery Course
Behavior of Complex Systems - PHYS 194
257 Loomis Lab
Alfred W Hubler, 244-5892
Our globally networked society has to deal with increasingly complex problems, yet our intuitive responses are often based on a linear way of thinking. The goal of this freshman discovery course is to showcase success stories of complex systems engineering and give the students an intuition on predicting and controlling complex systems. It will give students an incentive to enroll in math and science courses and to get a solid education in computer science.
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Examples of Complex Systems:
Important Mathematical Concepts:
- life, reproduction, and evolution of simple organisms
- chaos and catastropes
- earth quakes
- the spread of infections, including the spread of the HIV virus in a population, the spread of cancer cells in a body, the spread of new technologies and ideas
- the rise and fall of social organizations
- mixed reality systems
Important Computational Concepts:
Important Complex Systems Paradigms:
- deterministic chaos
- neural nets
- cellular automata
- genetic algorithms
- adapation to the edge of chaos
- minimum resistance
- control of chaos
- leadership paradigm
will be posted here (user name: guest, password: guest).
There are no exams.
- 60% of the grade is based on attendence
- 40% of the grade is based on a 4-page term paper
This courseware was created with support from NSF grant 0140179.