School of Computer Science

Module 06-19341 (2012)

Introduction to Natural Computation

Level 2/I

Xin Yao Semester 1 10 credits
Co-ordinator: Xin Yao
Reviewer: Jeremy Wyatt

The Module Description is a strict subset of this Syllabus Page.

Aims

The aims of this module are to:

  • introduce the field of natural computation
  • explore common themes and principles underlying different natural computation systems
  • provide a foundation for the further study of some specific techniques

Learning Outcomes

On successful completion of this module, the student should be able to:

  • explain and illustrate the key concepts of: de-centralisation, interaction, self-organisation, emergence
  • describe the common principles underlying a range of natural computation techniques
  • compare and contrast natural systems with their computational counterparts
  • show how natural computation techniques can be adapted to solving learning and optimisation problems
  • analyse the behaviour of natural computation systems

Teaching methods

2 hours of lectures per week


Assessment

  • Sessional: 1.5 hour examination (70%), continuous assessment (30%).
  • Supplementary: 1.5 hour examination (100%).

Detailed Syllabus

  1. Simple interaction models.
  2. Cellular automata, flocking.
  3. Interactions, games, co-operation.
  4. Diffusion models.
  5. Social behaviour (insects, humans).
  6. Networks of interaction.
  7. Evolution by Natural Selection.
  8. Genetic algorithms.
  9. Gene regulation and cell signaling.
  10. Neuronal interactions.
  11. Perceptrons.
  12. Other neural models.

Programmes containing this module