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 |
EMAT10007 and EMAT10006 or an equivalent introduction to computer programming unit |
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 artificial evolution, cellular systems, DNA computing, neural networks, developmental systems, artificial immune systems, swarm intelligence, and bio-inspired robotics.
Student will be able to;
- Explain the benefits and limitations of bio-inspired approaches.
- Extract basic principles from intelligent systems in nature that can be applied to engineering.
- Apply bio-inspired AI to engineer solutions for real world applications.
- Use insight from engineered systems to improve understanding of natural systems.
20 Lectures
10 x 1hr Computer Labs
2-hour written examination: 100% (all learning outcomes)
Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies, Dario Floreano and Claudio Mattiussi, MIT Press, 2008 http://baibook.epfl.ch