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> Cognitive Systems and Intelligent Technologies
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Cognitive Systems and Intelligent Technologies
Note:
Whilst every effort is made to keep the syllabus and assessment records correct
for this course, the precise details must be checked with the lecturer(s).
| Code: | 1009 |
| Year: | 1or 2 |
| Prerequisites: |
None |
| Term: | 2 |
| Taught By: | John Dowell (66.6%)
Denise Gorse (33.3%)
|
| Aims: | The word 'cognition' refers to knowledge, and cognitive systems are systems which possess and use knowledge. Searching the web for information to help you make a decision is an example of a cognitive system. So is a decision support system for clinicians, or an aircraft flight deck. This module explores how cognitive systems are able to solve complex problems and make decisions, how they are able to represent and use knowledge, how they are able to learn, to see and sense, to understand natural language, to store and reuse experience, and how they are able to organise shared activity. We compare how these capabilities can be achieved by computational systems with how they are achieved by humans. We examine the computational architectures that can produce these capabilities, with a particular emphasis on the contrasts between rule-based and neural network approaches. |
| Learning Outcomes: | Acquisition of the concepts and language of intelligent systems, and the ability to relate human and artificial intelligences. Understanding of the primary methods of cognitive science and their application. Knowledge of application areas of cognitive engineering |
Content:
| Future origins of Cognitive Science | |
| Computational origins of Cognitive Science | |
| Neural Networks and symbolic architectures | |
| Knowledge representation systems | |
| Problem solving systems | |
| Decision making systems | |
| Learning systems | |
| Vision Systems | |
| Natural Language Systems | |
| Applications of cognitive science | |
Method of Instruction:
Lecture presentations with associated groupwork and seminars.
Assessment:
The course has the following assessment components:
- Written Examination by Prior Disclosure (2.5 hours, 100%)
To pass this course, students must:
The examination rubric is:
Written examination by prior disclosure. Answer any 2 questions out of 6. All questions carry equal marks.Resources:
Stillings. 1995. Cognitive Science. MIT Press
Module website
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