Artificial Intelligence


To provide an introduction to the topic of Artificial Intelligence (AI) through studying problem-solving, knowledge representation, planning, and learning in intelligent systems.
To provide a grounding in the AI programming language Prolog.


Introduction (3 lectures): What is Artificial Intelligence? Characterisation of AI; historical overview; intelligent agents; agents’ environments; applications of AI; current state-of-the-art.

Recommended Texts

Reading lists are managed at Click here to access the reading lists for this module.

Learning Outcomes

(LO1) At the end of this module, students should be able to: identify or describe the characteristics of intelligent agents and the environments that they can inhabit;

(LO2) identify, contrast and apply to simple examples the major search techniques that have been developed for problem-solving in AI;

(LO3) distinguish the characteristics, and advantages and disadvantages, of the major knowledge representation paradigms that have been used in AI, such as production rules, semantic networks, propositional logic and first-order logic;

(LO4) solve simple knowledge-based problems using the AI representations studied;

(LO5) identify or describe approaches used to solve planning problems in AI and apply these to simple examples;

(LO6) identify or describe the major approaches to learning in AI and apply these to simple examples;

(LO7) identify or describe some of the major applications of AI;

(LO8) understand and write Prolog code to solve simple knowledge-based problems.

(S1) Numeracy/computational skills - Problem solving

(S2) Numeracy/computational skills - Reason with numbers/mathematical concepts

Learning Strategy

Teaching Method 1 - Lecture
Attendance Recorded: Not yet decided
Notes: 3 per week during semester

Teaching Method 2 - Laboratory Work
Attendance Recorded: Not yet decided