COMP47410 Computational Creativity

Academic Year 2020/2021

Computational Creativity (CC) is a new branch of Artificial Intelligence and
Cognitive Science that explores the potential of machines to perform tasks in ways
that would be considered creative if performed by a human, or to generate outputs
that would be considered novel and interesting if generated by a human. As a field,
CC focuses primarily on the latter, to explore the generative potential of machines
and to focus on the building of software systems that construct original artifacts
(whether linguistic – as in stories, poems, jokes, slogans, tweets, etc. – or visual –
such as collages, paintings, patterns etc. – or musical – such as jazz riffs, pieces of
classical music, etc.)
Given its focus on creativity in humans and machines, a course on CC necessarily
mixes elements of cognitive science, psychology and philosophy into its core
computational structure. The course should appeal to students with an interest in
creativity, or an interest in AI that is not served by courses that emphasis problem-
solving. The course will be delivered through lectures and practical sessions, and will
require students to build generative systems of their own. Weekly assignments will
dovetail with the course project, so that work initiated in the assignments (and
incrementally build upon each week) will be completed in the project.
Lectures will involve instruction, discussion and debate about the nature of creativity,
the potential of machines to be creative, and the practicalities of building creative
systems.

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Curricular information is subject to change

Learning Outcomes:

On successful completion of this module the learner will be able to:
1. Understand the relevant concepts in the philosophy of AI, psychology and
computer science as their pertain to human and machine creativity
2. Understand how the study of machines can inform our understanding of
human cognition, and vice versa, with relation to dominant theories
3. Build their own generative systems in a programming language like Java
(e.g. as in the construction of an automated Twitterbot)
4. Know how to access and re-use existing Creative systems on the Web
4. Understand how to evaluate generative/creative systems empirically

Indicative Module Content:

Foundational concepts of human and machine creativity, novelty and usefulness, P and H creativity, weak and strong computational creativity, mere generation, self-critiquing and filtering, evaluation of creative systems, generative grammars and systems, conceptual spaces

Student Effort Hours: 
Student Effort Type Hours
Lectures

24

Practical

18

Autonomous Student Learning

80

Total

122

Approaches to Teaching and Learning:
In-class discussions and debates, weekly assignments and homework, individual projects with in-class presentations and discussions 
Requirements, Exclusions and Recommendations
Learning Recommendations:

Artificial Intelligence (though not necessary)


Module Requisites and Incompatibles
Pre-requisite:
COMP30050 - Software Engineering Project 3


 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Continuous Assessment: Assignment 2 Throughout the Trimester n/a Graded No

8

Continuous Assessment: Assignment 4 Throughout the Trimester n/a Graded No

8

Project: Individual project involving design, implementation and final report Week 12 n/a Graded No

60

Continuous Assessment: Assignment 5 Varies over the Trimester n/a Graded No

8

Continuous Assessment: Assignment 1 Throughout the Trimester n/a Graded No

8

Continuous Assessment: Assignment 3 Throughout the Trimester n/a Graded No

8


Carry forward of passed components
Yes
 
Remediation Type Remediation Timing
In-Module Resit Prior to relevant Programme Exam Board
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Mr Philipp Wicke Tutor
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.

 
Spring
     
Lecture Offering 1 Week(s) - 18, 19, 20, 21, 22, 23, 24, 27, 28, 29, 30, 31 Mon 16:00 - 16:50
Lecture Offering 1 Week(s) - 18, 19, 20, 21, 22, 23, 24, 27, 28, 29, 30, 31 Thurs 16:00 - 16:50
Spring