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.
This class is taught using a flipped classroom methodology, meaning 1h lectures are watched at home in preparation for the course, and class-time is dedicated to hands-on activities and discussions including group work, pen and paper exercises, live-coding, and startup pitching.
Upon successful completion of the unit students will be able to;
20 Hands-on class-room activities
10 x 1hr Lecture preparation
30% Exercise hand-in
Students will need to hand in an exercise sheet done during the 2-hour hands-on classroom activities, on six occasions. It is expected that the material can be fully completed in class. Each hand-in is worth 5% of the mark for a total of 30%. (ILO 1-5)
70% Startup pitch and report
For the startup pitch and report, groups are expected to prepare a 3min startup pitch in the area of bio-inspired AI, which will be delivered in the final lecture. Pitches will be prepared and rehearsed during class time. In addition, everyone must hand in an independent report of 5 pages describing their startup idea, motivation, market, how the technology will work, and what ethical/societal considerations should be addressed. (ILO 1-5)
Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies, Dario Floreano and Claudio Mattiussi, MIT Press, 2008