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School of Engineering and Informatics (for staff and students)

The Ghost in the Machine (G5077)

Cognitive Science 1: The Ghost in the Machine

Module G5077

Module details for 2013/14.

15 credits

FHEQ Level 4

Library

Rather than a set text, students will read a selection of chapters and articles, such as: Jackson, Frank (1986). "What Mary Didn't Know". Journal of Philosophy (83): 291-295.
Searle, John (1980), "Minds, Brains and Programs", Behavioral and Brain Sciences 3 (3): 417-457
Turing, Alan (October 1950), "Computing Machinery and Intelligence", Mind LIX (236): 433-460

Module Outline

What is it to be an intelligent embodied person? We will look at a number of different `materialist' theories, concentrating on variants of the computer model, and on neurophysiologically based accounts of mind. In doing so, we will examine some of the basic issues underlying cognitive science as an interdisciplinary study of the mind, taking in topics from psychology, neurosicence, linguistics, computing, artificial intelligence, robotics, evolutionary theory, biology and philosophy along the way.

Module learning outcomes

Demonstrate familiarity with the basics of philosophical and methodological problems in cognitive science.

Demonstrate a basic grasp of the way different disciplines (eg psychology, neuroscience, linguistics, computer science and AI, robotics, biology, etc.) collaborate and compete together over their treatment of common themes in cognitive science.

Appreciate the importance of thinking and reasoning clearly, of expressing their ideas with clarity, and critically reflecting upon their own views and prejudices.

TypeTimingWeighting
Coursework100.00%
Coursework components. Weighted as shown below.
PresentationT1 Week 12 (10 minutes)30.00%
EssayA1 Week 2 70.00%
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.

TermMethodDurationWeek pattern
Autumn SemesterLecture1 hour111111111111
Autumn SemesterSeminar1 hour111111111111

How to read the week pattern

The numbers indicate the weeks of the term and how many events take place each week.

Dr Simon Bowes

Assess convenor
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School of Engineering and Informatics (for staff and students)

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