TDT22 - Complex and Biologically-Inspired Systems (2016).

Faglśrer: Stefano Nichele
Lecturer: Stefano Nichele, Donn Morrison, Gunnar Tufte
Students: List

Description: 'The whole is more than the sum of its parts', Aristotle

Complex systems are systems where the collective behavior of their parts entails emergence of properties that can hardly, if not at all, be inferred from properties of the parts. Examples of complex systems include ant-hills, ant themselves, human economies, climate, nervous systems, cells and living things, including human beings, as well as modern energy or telecommunication infrastructures.

This course will cover theory and some important aspects related to the modeling and analysis of complex systems. This knowledge will be useful also in your real life and at work. It will complete your top-down engineering skills with unconventional bottom-up techniques.

Keywords: Complex Systems, Unconventional Computation, Cellular Computation, Sparsely Connected Networks, Cellular Automata, State Space, Basin of Attraction, Boolean Networks, Emergent Properties, Biologically-Inspired Methods, Neural Networks, Agent-Based Models, Swarm, Evolution, Development, Life Universe and Everything.

Structure: Lectures are orginized as discussions on selected scientific publications. The introductory part of the course curriculum is fixed, while the students will expand the curriculum choosing additional scientific publications. Students can alternatively choose to develop a mini-complex system simulation project (very little/easy programming, working libraries given, see PyCX).

Syllabus 2016: (PRELIMINARY DATES)

29/08 Stefano (intro and planning, distribute papers, etc.)
1: Bar-Yam, The Dynamics of Complex Systems - Examples, Questions, Methods and Concepts (Everyone should read this before the startup meeting)

09/09 Donn
2: Newman, The Structure and Function of Complex Networks (exclude section 4, 5, and 6)
3: Garnier, The Biological Principles of Swarm Intelligence

26/09 Stefano
4: Sipper, The Emergence of Cellular Computing
5: Heylighen, The Science of Self-Organization and Adaptivity
6: Langton, Computation at the Edge of Chaos: Phase Transitions and Emergent Computation

10/10 Gunnar
7: Mitchell, Life and Evolution in Computers
8: Gershenson, Introduction to Random Boolean Networks
9: Doursat, A Review of Morphogenetic Engineering

24/10 Stefano
10: Sayama, Introduction to the Modeling and Analysis of Complex Systems, Chapter 1, 2, and 10
Demo (depending on number of students)

28/11 Exam (Stefano)

Additional reading only if you are interested (not part of syllabus):
Perez, Modeling Mountain Pine Beetle Infestation with an Agent-Based Approach at Two Spatial Scales
Yao, Evolving Artificial Neural Networks
Baranger, Chaos, Complexity, and Entropy. A Physics Talk for Non-Physicists
Bar-Yam, Complexity Rising: From Human Beings to Human Civilization, a Complexity Profile
Cooney, Beyond Contact Tracing: Community-Based Early Detection for Ebola Response
Franca, Visualizing the "Heartbeat" of a City with Tweets

During the startup meeting papers are distributed to students/groups. Each group should prepare a presentation on the given paper (approx. 20/30 min + 10/15 min discussion and questions). Everyone should read the paper before the presentation and partecipate in the discussion. Students/groups that are not presenting a paper will present a short demo (approx. 15 min) of their mini-project (see below). More info during the startup meeting.

Mini-Project/Demo, depending on number of students: (text not part of the syllabus)
From "Sayama, Introduction to the Modeling and Analysis of Complex Systems" choose one example among CA (Chapter 11), Network (Chapter 16) or ABM (Chapter 19) and execute/analyze/modify PyCX code, 10/15 min presentation/demo.
Book available here (free download).
PyCX available here (free download).

Editor: Stefano Nichele  Contact address: Stefano Nichele   Page updated: 03 08 2016