- Student Records
Programme & Unit Catalogues


EE40098: Computational intelligence

Follow this link for further information on academic years Academic Year: 2015/6
Further information on owning departmentsOwning Department/School: Department of Electronic & Electrical Engineering
Further information on credits Credits: 6
Further information on unit levels Level: Masters UG & PG (FHEQ level 7)
Further information on teaching periods Period: Semester 1
Further information on unit assessment Assessment Summary: CW 25%, EX 75%
Further information on unit assessment Assessment Detail:
  • Assignment (CW 25%)
  • Examination (EX 75%)
Further information on supplementary assessment Supplementary Assessment: EE40098 - Mandatory Extra Work (where allowed by programme regulations)
Further information on requisites Requisites:
Further information on descriptions Description: Aims:
To provide students with an understanding of some of the principles of Artificial Intelligence.

Learning Outcomes:
After completing this module, students should be able to: construct a simple rule based expert system; explain the major components of a fuzzy logic system and conduct fuzzy inference; describe the major type of neural networks and their learning algorithms; construct multilayer neural networks for pattern classification; apply a simple genetic algorithm to solve optimisation problems; construct and solve game trees for single player and multi-player games.

Skills:
Application of the techniques introduced in the lectures to AI problems: taught, facilitated and tested.

Content:
Expert Systems: Overview, rules , inference, knowledge aquisition, forward and backward chaining. Fuzzy Logic: Comparison with crisp logic. Linguistic variables, Degree of Membership, fuzzy rules, defuzzification. Neural Networks: MCP neuron, geometric interpretation. XOR problem. 1, 2, and 3 layer feed-forward networks. The Hebb rule, sigmoid function, backpropagation. Genetic Algorithms: Overview, the Schema Theorem, representation, populations, selection, crossover mutation. GameTheory: One and two player perfect information games, AND/OR game trees, depth first and breadth first searches, min-max search, alpha-beta pruning, proof number searching.
Further information on programme availabilityProgramme availability:

EE40098 is Compulsory on the following programmes:

Department of Electronic & Electrical Engineering
  • UEEE-AFM13 : MEng(Hons) Computer Systems Engineering (Year 4)
  • UEEE-AKM13 : MEng(Hons) Computer Systems Engineering with Year long work placement (Year 5)
  • UEEE-AFM12 : MEng(Hons) Electrical Power Engineering (Year 4)
  • UEEE-AKM12 : MEng(Hons) Electrical Power Engineering with Year long work placement (Year 5)
Department of Mechanical Engineering

EE40098 is Optional on the following programmes:

Department of Electronic & Electrical Engineering
  • UEEE-AFM01 : MEng(Hons) Electrical and Electronic Engineering (Year 4)
  • UEEE-AKM01 : MEng(Hons) Electrical and Electronic Engineering with Year long work placement (Year 5)
  • UEEE-AFM05 : MEng(Hons) Electronic and Communication Engineering (Year 4)
  • UEEE-AKM05 : MEng(Hons) Electronic and Communication Engineering with Year long work placement (Year 5)
  • UEEE-AFM14 : MEng(Hons) Electronic Engineering with Space Science & Technology (Year 4)
  • UEEE-AKM14 : MEng(Hons) Electronic Engineering with Space Science & Technology with Year long work placement (Year 5)
  • UEXX-AFM02 : MEng(Hons) Integrated Mechanical and Electrical Engineering (Year 4)
  • UEXX-AKM02 : MEng(Hons) Integrated Mechanical and Electrical Engineering with Year long work placement (Year 5)
Department of Mathematical Sciences
Notes:
* This unit catalogue is applicable for the 2015/16 academic year only. Students continuing their studies into 2016/17 and beyond should not assume that this unit will be available in future years in the format displayed here for 2015/16.
* Programmes and units are subject to change at any time, in accordance with normal University procedures.
* Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.