Module 28209 (2019)
Module description - Nature Inspired Search and Optimisation
The Module Description is a strict subset of the Syllabus Page.
|Module Title||Nature Inspired Search and Optimisation|
|School||School of Computer Science|
|Member of Staff||Shan He Per Kristian Lehre|
|Semester||Semester 2 - 10 credits|
Large Group Lectures
Natural Computation is the study of computational systems that use ideas and get inspiration from a variety of natural systems. Its powerful techniques can be applied not only to optimisation but also learning and design. Many such techniques can be characterised as general randomised search heuristics which are the method of choice in practical optimisation scenarios where no good problem-specific algorithms are available.Topics covered in this module focus on nature-inspired optimisation techniques. Where appropriate, the methods discussed are related to other approaches and application areas. Example topics covered include variants of local search, evolutionary computation, swarm intelligence and artificial immune systems. While the focus is on the applications of such techniques, theoretical foundations are also briefly studied.
On successful completion of this module, the student should be able to:
Sessional: 1.5 hr Examination (90%), Continuous Assessment (10%)
Supplementary (where allowed): 1.5 hr Examination (100%)