Course Details in 2022/23 Session

Module Title	LM Complex Adaptive Systems (Extended)
School	Computer Science
Department	Computer Science
Module Code	06 30237
Module Lead	Shan He
Level	Masters Level
Credits	20
Semester	Semester 1
Pre-requisites
Co-requisites
Restrictions	None
Contact Hours	Lecture-33 hours Guided independent study-167 hours Total: 200 hours
Exclusions
Description	Many natural and artificial systems, such as brains or the Internet, are characterized by complex behaviours that emerge from interactions between a large number of simpler components. These systems are collectively called complex adaptive systems (CAS). In this module, we will study the basic concepts, theories and methods for designing and understanding CAS. Example topics covered include artificial life, evolutionary computation, swarm intelligence and artificial neural networks.
Learning Outcomes	By the end of the module students should be able to: explain and illustrate the key concepts and common principles of complex adaptive systems and behaviours compare and contrast natural systems with their computational counterparts show how complex adaptive systems and behaviours can be adapted to solve learning and optimisation problems analyse the behaviour of complex adaptive systems The student should demonstrate the capacity to independently study, understand, and critically evaluate advanced materials or research articles in the subject areas covered by this module.
Assessment
Assessment Methods & Exceptions	Main Assessments: 1.5 hour examination (50%) and continuous assessment (50%) Supplementary Assessments: 1.5 hour examination (50%) and continuous assessment (50%)
Other
Reading List