| Unit name | Bio-Inspired Artificial Intelligence |
|---|---|
| Unit code | EMATM0029 |
| Credit points | 10 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Professor. Hauert |
| Open unit status | Not open |
| Pre-requisites |
None |
| Co-requisites |
None |
| School/department | School of Engineering Mathematics and Technology |
| Faculty | Faculty of Engineering |
Nature has found clever solutions for the design of intelligent systems. Chemical networks, cells, brains and societies are able to self-organise to perform seemingly complex tasks. These behaviours result from evolution, development, and learning.
With this course we aim to take inspiration from nature to engineer intelligent systems for real-world applications. Each lecture looks at a biological system and extracts basic principles that can be implemented in reality. Topics covered include neural networks, machine learning, artificial evolution, cellular systems, DNA computing, swarm intelligence, and bio-inspired robotics.
Upon successful completion of the unit students will be able to;
Teaching will be delivered through a combination of synchronous and asynchronous sessions, including lectures, supported by live online sessions, problem sheets and self-directed exercises.
1 Summative Assessment, 100% - Coursework. This will assess all ILOs.
Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies, Dario Floreano and Claudio Mattiussi, MIT Press, 2008. http://baibook.epfl.ch
