Artificial Intelligence Methods
| Code | School | Level | Credits | Semesters |
| COMP2024 | Computer Science | 2 | 20 | Spring Malaysia |
- Code
- COMP2024
- School
- Computer Science
- Level
- 2
- Credits
- 20
- Semesters
- Spring Malaysia
Summary
This module builds on the first year Fundamentals of AI, which covers the ACM learning outcomes, and introduces new areas. The emphasis is on building on the AI research strengths in the School. It gives brief introductions to topics including AI techniques, fuzzy logic and planning, and modern search techniques such as, Iterated Local Search, Tabu Search, Simulated Annealing, Evolutionary Algorithms, Genetic Programming and Hyper-heuristics, etc. Students will also explore the implementation of some AI techniques.
Target Students
Compulsory for Part I Computer Science and Artificial Intelligence students. Available to other Part I undergraduate students in the School of Computer Science. Not available to students taking G52AMI.
Classes
- One 2-hour lecture each week for 12 weeks
- One 2-hour computing each week for 12 weeks
Activities may take place every teaching week of the Semester or only in specified weeks. It is usually specified above if an activity only takes place in some weeks of a Semester
Assessment
- 50% Coursework 1: Software implementation of the techniques taught in the lectures applied to a problem specified.
- 50% Exam 1 (2-hour): 120 minutes written examination
Educational Aims
To build on first year AI module and further an appreciation of various AI techniques. To understand and implement a software solution of AI techniques.Learning Outcomes
Knowledge and Understanding:
Ability to describe some advanced AI techniques and have a good understanding of those techniques.
Intellectual Skills:
Understand and describe various AI techniques and where they might be applied.
Professional Skills:
Enhanced skills to write software to implement an AI method, the ability to evaluate available AI tools and techniques and select those appropriate to a given situation.
Transferable Skills:
Problem solving, ability to compare and contrast based on understanding and experience of AI programming tools and techniques.
Conveners
- Dr Chye Cheah Tan
- Dr Tissa Chandesa