School of Computing

Module details

CO837 Natural Computation (15 credits)

Syllabus

There is an increasing use of nature-inspired computational techniques in computer science. These include the use of biology as a source of inspiration for solving computational problems, the application of artificial intelligence techniques to various problems, and the use of physical, chemical and biological and systems to construct computers. It is therefore proposed to allow students the opportunity to become exposed to these ideas for use in their late careers.

  • Introductory material.
    Is computer science the study of computers as products of human ingenuity or the study of natural processes? Is computing actually a property of the natural world? Is it possible to interpret natural phenomena using computational concepts?  The use of metaphor, model and inspiration in computer science. Issues concerning scientific method and methodology.  What sort of scientific questions can we answer using computational and informational concepts? Examples of biological problems that can be tackled using computational concepts (not computer simulation of biosystems).  Using computational properties of the world directly for problem solving.
  • Evolutionary computing.
    General context via the idea of biologically-inspired computing techniques. Genetic algorithms: basic ideas, details of selection, crossover, mutation algorithms, how to choose between various types of algorithms. Genetic programming.
  • Artificial immune systems.
    Background to the biological immune system, how these ideas are abstracted to create AISs. Framework for AIS design. Applications.
  • Swarm intelligence.
    Basic ideas. Ant colony optimization. Particle swarm optimization. Applications.
  • Computation based on chemistry.
    Exploiting properties of chemicals to do computing. DNA computing and applications. Wavefront computing and applications.
  • Artificial life and simulated biology.
    The distinction between using computers to study existing biological systems and using them to investigate what life in general could be like. Reasons for using computers in biology. Applications of artificial life and biological simulation in a number of biological and medical areas; e.g. ecology, evolution, molecular biology, and/or cancer research. Theoretical notions  such as emergence and the complex systems stance towards the natural world.

Note

This web page provides advance information about a module due to run in the coming academic year. We believe the details are accurate at the time of writing but they may be subject to change.

School of Computing, University of Kent, Canterbury, Kent, CT2 7NF

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Last Updated: 08/04/2011 15:43