06-14409
Behaviour of Complex Systems

Level M

Dr L Jankovic

10 credits in Sem2

The School of Computer Science Module Description is a strict subset of this Syllabus Page. (The University module description has not yet been checked against the School's.)

Changes and Updates

No major changes during the current academic year.

2 July 2003: Most recent update.

Outline

The module gives a hands-on introduction into the Science of Complexity, and investigates how simple rules applied to system components create the richness and diversity of natural and man-made systems.

Aims

The aims of this module are to:

Give a hands-on introduction into the Science of Complexity.
Investigate how simple rules applied to system components create the richness and diversity of natural and man-made systems.
Analyse self-organisation and other principles of complexity at work in a variety of systems, from molecular and biological systems to computer networks, and business and economic systems.
Stimulate students to familiarise themselves with the principles of complexity by building simple models of complex systems using examples from lectures as building blocks.

Learning Outcomes

On completion of this module, the student should be able to:	Assessed by:
Demonstrate a good understanding of principles of complexity and behaviour of complex systems.	Examination
Apply this understanding to modelling, analysis and problem solving in a variety of natural and man-made complex systems.	Practical work

Restrictions, Prerequisites and Corequisites

Restrictions:

Maximum of 30 students

Prerequisites:

None

Co-requisites:

None

Teaching

Teaching methods:

2 hrs per week lectures/tutorials per week

Contact hours:

Assessment

2 hr examination (50%), continuous assessment (50%). Resit (where allowed) by examination only.

The continuous assessment consists of a mini-project.

Recommended Books

Title	Author(s)	Publisher, Date	Comments
A New Kind of Science	Stephen Wolfram	Wolfram Media, Inc., 2002
At Home in the Universe: The Search for Laws of Self-Organization and Complexity	Stuart Kauffman	Oxford University Press, 1996
Hidden Order: How Adaptation Builds Complexity	John H. Holland	Addison-Wesley, 1996
Dynamics of Complex Systems	Yaneer Bar-Yam	New England Complex Systems Institute, 1997

Detailed Syllabus

Introduction and objectives. Definition and fundamentals of complexity. Emergent behaviour of equilibrium and non-equilibrium systems. Examples.
Phase transition between order and chaos. Spontaneous self-organisation and support for generalised computation. Examples.
Autocatalytic networks. Sub and supercritical connectivity, and behaviour in the phase transition region. Catalytic closure. Emergent and self-sustainable behaviour of Boolean, chemical, and other networks, and how life may have started. Examples.
Genetic circuits and attractors of spontaneous order. Infinite genome spaces versus finite cell types. Examples.
Genotype spaces and fitness landscapes. Diminishing returns. The limits of selection driven evolution. The coupling of selection and self-organisation. Examples.
Design of organisms and artefacts through search of fitness landscapes. Learning curves. Examples.
Self-organisation and tuning of ecological and technological systems. Origins and avalanches of extinction. Examples.
Self-organisation and dynamics of companies, economies, and political systems. Homogeneous and heterogeneous systems, and systems in the phase transition. Examples.
Self-sustained expansion and unfolding of technological frontiers. The driving forces of technological and economic growth. Examples.
Integration and formulation of principles of Complexity. Conclusions.

Relevant Links

None.

Page maintained by:	Dr L Jankovic
Content last updated:	2 July 2003
Source:	/resources/modules/2003/xml/14409.xml

06-14409Behaviour of Complex Systems