Course co-ordinator(s): Prof Michael Lones (Edinburgh), Dr Wei Pang (Edinburgh), Assoc Prof. Hadj Batatia (Dubai), Claudio Zito (Dubai).
Aims:
Traditional computation finds it either difficult or impossible to perform a certain key range of tasks associated with pattern recognition, problem solving and autonomous intelligence. Great progress towards designing software for such tasks has emerged by taking inspiration from a range of natural, mainly biological, systems.
The aims of this course are to:
- introduce an appreciation of the former
- introduce the main biologically-inspired algorithms and techniques which are now commonly researched and applied
- establish a practical understanding of the real-world problems to which these techniques may be fruitfully be applied.
Detailed Information
Course Description: Link to Official Course Descriptor.
Pre-requisite course(s): F29AI Artificial Intelligence and Intelligent Agents or equivalnt.
Location: Dubai, Edinburgh.
Semester: 1.
Syllabus:
- classical vs. biologically-inspired computation,
- evolutionary algorithms (basic EA design, and how they are applied to a wide range of problems)
- swarm intelligence (ant colony methods, particle swarm optimisation)
- neural computation (perceptrons, multilayer perceptrons, associative networks)
- cellular automata
SCQF Level: 11.
Credits: 15.