Intelligence in Animals and Machines (980G5Z)
Note to prospective students: this content is drawn from our database of current courses and modules. The detail does vary from year to year as our courses are constantly under review and continuously improving, but this information should give you a real flavour of what it is like to study at СÀ¶ÊÓƵ.
We’re currently reviewing teaching and assessment of our modules in light of the COVID-19 situation. We’ll publish the latest information as soon as possible.
Intelligence in Animals and Machines
Module 980G5Z
Module details for 2024/25.
15 credits
FHEQ Level 7 (Masters)
Module Outline
The module will develop an understanding of what it means for an animal or a machine to behave intelligently, and how brain and behavioural systems are adapted to enable an animal to cope effectively within its environment. We consider diverse aspects of intelligence including navigation and motor control, tool-use, language, memory and social skills. We ask how these are related to one another and how they are matched to the particular needs of animals. We finally consider what we can learn about intelligence through computational modelling by examining the challenges faced by scientists trying to create artificial systems with the same behavioural capabilities.
As well as the reading list, three papers on current research issues will be given each week to be discussed in seminars.
As well as the reading list, several papers on current research issues will be given each week to be discussed in seminars. In addition, a couple of papers which give you the flavour of the course are:
Shettleworth, S. Clever animals and killjoy explanations in comparative psychology. Trends in Cognitive Sciences, 2010
Webb, B. What does robotics offer animal behaviour? Animal Behaviour, 2000
Module learning outcomes
Demonstrate a systematic understanding of the meanings of the term 'intelligence', and an ability to critically evaluate experimental data and theoretical concepts in the field.
Synthesise research in animal cognition and the engineering of artificial intelligence, critically assess how these disciplines inform one another and evaluate the appropriateness of the methodologies used to do this.
Present a written account of specific aspects of the course subject matter based on independent reading of primary scientific and engineering literature, in the context of the wider reading of more general texts.
Develop and argue an original hypothesis that draws from the major themes of the course.
| Type | Timing | Weighting |
|---|---|---|
| Unseen Examination | Semester 1 Assessment Week 1 Wed 13:30 | 60.00% |
| Coursework | 40.00% | |
| Coursework components. Weighted as shown below. | ||
| Report | PS2 Week 1 | 100.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
Please note that the University will use all reasonable endeavours to deliver courses and modules in accordance with the descriptions set out here. However, the University keeps its courses and modules under review with the aim of enhancing quality. Some changes may therefore be made to the form or content of courses or modules shown as part of the normal process of curriculum management.
The University reserves the right to make changes to the contents or methods of delivery of, or to discontinue, merge or combine modules, if such action is reasonably considered necessary by the University. If there are not sufficient student numbers to make a module viable, the University reserves the right to cancel such a module. If the University withdraws or discontinues a module, it will use its reasonable endeavours to provide a suitable alternative module.