COMP209P - Cognitive Systems and Intelligent Technologies
This database contains the 2017-18 versions of syllabuses. Syllabuses from the 2016-17 session are available here.
Note: Whilst every effort is made to keep the syllabus and assessment records correct, the precise details must be checked with the lecturer(s).
|Year||1 or 2|
|Taught By||John Dowell (66.6%) |
Denise Gorse (33.3%)
|Aims||To introduce the study and development of intelligent systems, including the correspondence with natural cognitive systems and the design of smart tools.|
|Learning Outcomes||Students will understand foundational theories, methods, and technologies involved in artificial intelligence and in cognitive systems science. They will recognize the primary themes and issues involved in creating intelligent technologies and smart tools. The structural dimensions of intelligent agents will be examined in relation to the capabilities they support in different environments. Symbolic and sub-symbolic architectures will be examined and contrasted. Students will understand the theoretical and technical challenges involved in modelling and building systems that can reason, solve problems, acquire and use knowledge, make decisions, perceive their environment and communicate in natural language. They will learn how computational models can be used to help us understand human intelligence and about the smart technologies that extend that intelligence.|
- Cognition, systems, intelligence
- Intelligent agents
- Agent architectures
- Problem solving
- Knowledge representation
- Sensing and communicating
Method of Instruction
Lecture presentations only, 3 hours in each week for eight weeks
The course has the following assessment components:
- 2-hour 'seen' examination - i.e. written examination by prior disclosure (100%)
To pass this course, students must:
- Obtain an overall pass mark of 40% for all components combined.
Reading list available via the UCL Library catalogue.