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Unit information: Bio-Inspired Artificial Intelligence in 2015/16

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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 Dr. Hauert
Open unit status Not open

EMAT10007 and EMAT10006 or an equivalent introduction to computer programming unit



School/department Department of Engineering Mathematics
Faculty Faculty of Engineering

Description including Unit Aims

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.

Intended Learning Outcomes

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.

Teaching Information

20 Lectures

10 x 1hr Computer Labs

Assessment Information

2-hour written examination: 100% (all learning outcomes)

Reading and References

Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies, Dario Floreano and Claudio Mattiussi, MIT Press, 2008