CE310-6-PT-CA:
Evolutionary Computation and Genetic Programming

The details
2019/20
Computer Science and Electronic Engineering (School of)
Colchester Campus & Apprenticeship Location
Spring Special
Undergraduate: Level 6
Current
Monday 13 January 2020
Friday 26 June 2020
15
07 May 2019

 

Requisites for this module
(none)
(none)
(none)
(none)

 

(none)

Key module for

(none)

Module description

This module will give an introduction to: evolutionary computation and genetic programming; evolutionary algorithms & their relationships; genetic programming compared to evolutionary algorithms, and in the process identify good genetic programming techniques to control parameter settings.

Module aims

The aim of this module is to give an introduction to the main techniques of evolutionary computation and genetic programming including: evolutionary algorithms & their relationships; genetic programming versus evolutionary algorithms; identify good genetic programming techniques; and identify good parameter settings.


Module learning outcomes

After completing this module, students will be expected to be able to:

1. Demonstrate an understanding of evolutionary algorithms and their relationships.
2. Demonstrate an understanding of genetic programming and its relationship with other evolutionary algorithms.
3. Categorise typical genetic programming application domains and associate these with good genetic programming techniques.
4. Determine the right parameter settings and specialise existing genetic programming operators, representations and fitness functions for specific applications.

Module information

Outline Syllabus

Evolution in Nature
Evolution Strategies
Genetic Algorithms
The basics of Genetic Programming (GP)
Fitness functions in GP
Advanced Representations
Code growth and methods to control it
Applications of GP.
Criteria for human-competitive machine intelligence and review of GP's human-competitive results
Advanced techniques and tricks of the trade.

Learning and teaching methods

Lectures, classes and laboratories

Bibliography

  • Poli, Riccardo; Langdon, W. B.; McPhee, Nicholas F.; Koza, John R. (2008) A field guide to genetic programming, [S.I.]: lulu.com.

The above list is indicative of the essential reading for the course. The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students. Further reading can be obtained from this module's reading list.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting
Coursework   Progress Test - wk 19    33.33% 
Coursework   Mini project    66.67% 
Exam  Main exam: 180 minutes during Early Exams 

Exam format definitions

  • Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
  • In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
  • In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
  • In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary, for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.

Your department will provide further guidance before your exams.

Overall assessment

Coursework Exam
30% 70%

Reassessment

Coursework Exam
30% 70%
Module supervisor and teaching staff
Prof Reinhold Scherer, email: r.scherer@essex.ac.uk.
Professor Reinhold Scherer
CSEE School Office, email: csee-schooloffice (non-Essex users should add @essex.ac.uk to create full e-mail address), Telephone 01206 872770

 

Availability
No
No
No

External examiner

Dr Iain Phillips
Loughborough University
Resources
Available via Moodle
Of 33 hours, 32 (97%) hours available to students:
1 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).

 

Further information

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