COMP219
Artificial Intelligence
Aims
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.
Syllabus
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
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
Description:
Attendance Recorded: Not yet decided
Notes: 3 per week during semester
Teaching Method 2 - Laboratory Work
Description:
Attendance Recorded: Not yet decided