COMP30290 Natural Computing 2013

Module Coordinators: Dr. Michael O'Neill and Dr. Miguel Nicolau

Description:

The field of Natural Computing has advanced rapidly over the past decade. One offshoot of this progress has been the development of a large family of algorithms inspired by Nature, including Biological, Social and Physical systems. Broadly speaking, these algorithms draw metaphorical inspiration from diverse sources, including the operation of biological neurons, processes of evolution, models of social interaction amongst organisms, and natural immune systems, in order to develop tools for solving real-world problems. This module provides an introduction to a broad range of Natural Computing algorithms and illustrates how they can be applied to real-world problems using a series of case studies.

In addition to teaching the essentials of Natural Computing, the module provides experience in the planning, executing, writing up, and critical evaluation of research.

Learning Outcomes:

On completion of the module students should be able to:

Assessment Strategies:

This is a 100% continuous assessment module. Each student undertakes an individual project, and writes up their work in the form of a 10-page conference-style paper.

Contact Hours:


Deadlines & Announcements


Module Materials


Recommended Reading

The type of project you undertake in this module will largely guide the depth in which you approach one of the Natural Computing methods. Some recommendations for the main methods follow.


Useful Links