Theory and Practice of Symbolic Artificial Intelligence
The overall aim of this module is to provide an in-depth study of a
range of ideas, theories and techniques used in the construction of
symbolic artificial intelligence systems. The module will be oriented
towards the creation of AI systems for tasks in the areas of
intelligent modelling, problem-solving, learning, decision-making,
reasoning and others. There is a large practical element to the module
with the students gaining experience in developing artificial
intelligence models. Theory and practice are intimately intertwined in
the field of Artificial Intelligence and this module is going to
reflect this.
The module does not presuppose prior knowledge on Artificial
Intelligence, but, as advanced module, participants will be expected
to invest the relevant work to keep pace with the covered material.
Course Material
Lectures
- Introduction (ps/pdf)
- Propositional Logic (ps/pdf)
- History of AI (Powerpoint)
- Predicate Logic (ps/pdf)
- Introduction to Prolog (ps/pdf)
- Prolog Rules (ps/pdf)
- Prolog Philosophy (ps/pdf)
- Structures in Prolog (ps/pdf)
- Operators (ps/pdf)
- Cut, Fail and Negation (ps/pdf)
- Meta-Predicate, Functor Manipulation and Assertion (ps/pdf)
- Search (pdf)
- Advanced Search and Games (pdf)
- Expert Systems (ps/pdf)
- Probability Theory
- Bayesian Networks
- Information Theory (ps/pdf)
Last changed at Fri Mar 24 14:43:10 2006 by D. Polani
Department of Computer Science