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Curricular information is subject to change
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
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 Type | Hours |
---|---|
Lectures | 24 |
Practical | 18 |
Autonomous Student Learning | 80 |
Total | 122 |
Artificial Intelligence (though not necessary)
Description | Timing | Component Scale | % 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 |
Remediation Type | Remediation Timing |
---|---|
In-Module Resit | Prior to relevant Programme Exam Board |
• Feedback individually to students, post-assessment
Not yet recorded.
Name | Role |
---|---|
Mr Philipp Wicke | Tutor |