Artificial Intelligence (H) is an introduction to Artificial Intelligence, giving the students an overview of intelligent agent design.

3 hours per week

Artificial Intelligence (M)

None

Examination 75%; Continuous assessment- practical exercises 25%.

It is the default expectation that all courses will offer opportunities for reassessment or deferred assessment. Where it is not possible to offer this in some assessment components, the grade achieved at the first attempt will be counted towards the final course grade, and any exceptions for this course are described below.

[No exceptions]

The aim of this course is to provide an overview of intelligent agent design, where agents perceive their environment and act rationally to fulfil their goals. Students will gain practical experience in labs, programming various aspects of intelligent systems.

By the end of the course students will be able to:

1. Demonstrate familiarity with the history of AI, philosophical debates, and understand the potential and limitations of the subject in its current form;

2. Explain the basic components of an intelligent agent, and be able to map these onto other advanced subjects such as information retrieval, computer vision, database systems, robotics, human-computer interaction, reactive systems etc

3. Discuss difficulties in computer perception;

4. Discuss basic issues in planning;

5. Explain and apply search-based problem-solving techniques;

6. Formulate and apply Bayesian networks in modelling and planning;

7. Explain and apply utility theory as a probabilistic framework for rational decision making;

8. Explain and apply basic machine learning techniques to learn from rewards and observations.