Core Module Information
Module title: Emergent Computing for Optimisation

SCQF level: 11:
SCQF credit value: 20.00
ECTS credit value: 10

Module code: SET11508
Module leader: Emma Hart
School School of Computing, Engineering and the Built Environment
Subject area group: Computer Science
Prerequisites

There are no pre-requisites for this module to be added

Description of module content:

The module will address: - Why some problems are hard to solve - Modern heuristic search methods such as Evolutionary Algorithms, including evolution strategies; meta-heuristic search techniques such as tabu-search, simulated annealing, iterated local search; ant-colony optimisation; hyper-heuristics and associated methods. - Appropriate experimental methodologies for testing and analysing emergent computing algorithms- Simple statistical methods for evaluating the results

Learning Outcomes for module:

Upon completion of this module you will be able to

LO1: Critically evaluate the use of emergent computing algorithms in practical applications.

LO2: Critically assess the use of different algorithms in different problem domains.

LO3: Specify, customise and use appropriate algorithms for particular practical problems.

LO4: Apply an appropriate scientific approach to testing and analysing emergent computing algorithms and be able to use simple statistics to evaluate the results.

LO5: Present the results in an appropriate form and draw appropriate conclusions.

Full Details of Teaching and Assessment
2024/5, Trimester 1, In Person,
VIEW FULL DETAILS
Occurrence: 001
Primary mode of delivery: In Person
Location of delivery: MERCHISTON
Partner:
Member of staff responsible for delivering module: Emma Hart
Module Organiser:


Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)NESH Description
Face To Face Practical classes and workshops 10 Practical classes and workshops
Face To Face Tutorial 10 TUTORIAL
Face To Face Lecture 20 LECTURE
Face To Face CLASS TEST 2 Class Test
Online Guided independent study 158 Guided independent study
Total Study Hours200
Expected Total Study Hours for Module200


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words Description
Class Test 25 1~2 Week 13 HOURS= 2 hours Class test
Report 75 3~4~5 Week 13 , WORDS= 6 pages Report
Component 1 subtotal: 75
Component 2 subtotal: 25
Module subtotal: 100

Indicative References and Reading List - URL:
Contact your module leader