CSC3423 : Biologically-inspired Computing
- Offered for Year: 2017/18
- Module Leader(s): Dr Jaume Bacardit
- Owning School: Computing Science
- Teaching Location: Newcastle City Campus
|Semester 1 Credit Value:||10|
1) To familiarise students with computational concepts and methods inspired by biological systems
2) To introduce the concepts of algorithm design for biologically inspired computing
3) To develop skills in biologically inspired algorithm design with an emphasis on solving real world problems
4) To understand the most appropriate types of algorithms for different data analysis problems and to introduce some of the most appropriate implementation strategies.
Outline Of Syllabus
1. Brief introduction to biological systems and computational tasks of such systems.
2. Evolutionary Computation
3. Swarm Intelligence
4. Neural Networks
5. Membrane Computing
6. DNA Computing
7. Cellular Automata and Artificial Life
|Guided Independent Study||Assessment preparation and completion||22||0:30||11:00||Revision for end of Semester exam|
|Guided Independent Study||Assessment preparation and completion||10||1:00||10:00||Coursework|
|Guided Independent Study||Assessment preparation and completion||22||1:00||22:00||Lecture follow-up|
|Scheduled Learning And Teaching Activities||Lecture||22||1:00||22:00||Lectures|
|Scheduled Learning And Teaching Activities||Practical||10||1:00||10:00||Practicals|
|Guided Independent Study||Independent study||25||1:00||25:00||Background reading|
Teaching Rationale And Relationship
Lectures will be used to introduce the basic material and the more advanced theoretical topics.
Practical sessions, mostly computer based, will give the student opportunity to build up skills in algorithm design development and implementation.
The format of resits will be determined by the Board of Examiners
|Written exercise||1||M||10||Coursework strategy proposal (1000 words)|
|Written exercise||1||M||40||Final coursework report (2000 words)|
Assessment Rationale And Relationship
The exam will test the knowledge of novel and existing biologically inspired algorithms.
The practical will test skills in algorithm design and solving real world problems.
Study abroad students may request to take their exam before the semester 1 exam period, in which case the length of the exam may differ from that shown in the MOF.
N.B. This module has both “Exam Assessment” and “Other Assessment” (e.g. coursework). If the total mark for either assessment falls below 35%, the maximum mark returned for the module will normally be 35%.
- Reading List Website : rlo.ncl.ac.uk