Intelligent Systems I: 2008-2009
Lecturer | |
Degrees | Schedule B2 — Computer Science Schedule B2 — Mathematics and Computer Science ECS Part II — MEng Engineering and Computing Science |
Term | Michaelmas Term 2008 (16 lectures) |
Overview
To teach students the principal issues that arise in the theory, implementation and application of intelligent software systems. Here "intelligent systems" will be taken to mean those that have the ability to represent and reason about complex tasks given limited computational resources.Synopsis
- Fundamental Issues. Possibility of achieving intelligent behaviour; objections to intelligent systems; the Turing test; rational actions. [2]
- Search. Problem solving as search; search strategies; informed search methods. [3]
- Planning and scheduling. [3]
- Introduction to probabilistic reasoning. Probability theory; Bayes' theorem; Bayesian Networks; Markov processes. [4]
- Practical systems. Dealing with extent. Case studies. [3]
Syllabus
Fundamental issues in intelligent systems. Searching and planning. Introduction to probabilistic reasoning: Bayes rule, forward inference, and the Kalman filter. Dealing with uncertainty and geometry for physical agents.Reading list
- Bratko, Prolog Programming for Artificial Intelligence (3rd ed), Addison-Wesley, 2000.
- S.J. Russell and P. Norvig, Artificial Intelligence: A Modern Approach (2nd ed), Prentice-Hall, 2001.
Taking our courses
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Other matriculated University of Oxford students who are interested in taking this, or other, courses in the Department of Computer Science, must complete this online form by 17.00 on Friday of 0th week of term in which the course is taught. Late requests, and requests sent by email, will not be considered. All requests must be approved by the relevant Computer Science departmental committee and can only be submitted using this form.