Unit name | Artificial Intelligence (Teaching Unit) |
---|---|
Unit code | COMS30014 |
Credit points | 0 |
Level of study | H/6 |
Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
Unit director | Dr. Ray |
Open unit status | Not open |
Units you must take before you take this one (pre-requisite units) |
COMS10016 Imperative and Functional Programming and COMS10017 Object-Oriented Programming and Algorithms I or equivalent COMS10014 Mathematics for Computer Science A and COMS10013 Mathematics for Computer Science B or equivalent COMS20011 Data-Driven Computer Science or equivalent Programming paradigms, mathematics (including statistics, probability and algebra), and also desirable basic ideas of data mining/analysis |
Units you must take alongside this one (co-requisite units) |
EITHER Assessment Unit COMS30013 Artificial Intelligence (10 credit examination assessment) OR COMS30062 Artificial Intelligence (15 credit coursework assessment). Please note: COMS30014 is the Teaching Unit for the Artificial Intelligence option. Single Honours Computer Science and Mathematics and Computer Science students can choose to be assessed by either examination (10 credits, COMS30013) or coursework (15 credits, COMS30062) by selecting the appropriate co-requisite assessment unit. Any other students that are permitted to take the Artificial Intelligence option are assessed by examination (10 credits) and should be enrolled on the co-requisite exam assessment unit (COMS30013). |
Units you may not take alongside this one | |
School/department | School of Computer Science |
Faculty | Faculty of Engineering |
Artificial Intelligence (AI) systems and tools are virtually everywhere around us at present, no longer being just ‘science fiction’. Since Alan Turing, considered as the father of AI, postulated the question “can machines think?”, the world has witnessed innumerable advances in the field. “Thinking machines” are continuously developed worldwide to contribute to the societal good, in many aspects and sectors like economy, sustainability, safety, fairness, education, health, manufacturing and entertainment, to name a few. But, what are the foundations behind these “thinking machines” and intelligent tools?
This unit introduces the field of AI and its foundational principles, techniques and algorithms. It firstly covers the basics of knowledge representation and reasoning, followed by AI methods for search and optimisation. These foundations are then used in the second half of the unit, where the paradigm of intelligent agents, multi-agent systems and automated planning techniques are covered.
We will introduce and explore the main paradigms behind AI:
We will also apply the above paradigms to define AI agents or teams of them to solve challenging real-world tasks or complex problem-solving games that would normally require capabilities resembling human intelligence.
Successful completion of the unit will enable students to:
When assessed by Examination, in addition to the general ILOs above, the student will be also able to:
OR
When assessed by Coursework, in addition to the general ILOs above, the student will be also able to:
Teaching will be delivered through a combination of synchronous and asynchronous sessions, including lectures, practical activities supported by drop-in sessions, problem sheets and self-directed exercises.
Teaching will take place over Weeks 1-7, with coursework support in weeks 9-11 and for students assessed by examination, consolidation and revision sessions in Weeks 12.
Examination details:
2 hour exam (100%, 10 credits)
OR
Coursework details:
Coursework (100%, 15 credits) - to be completed during a specific period.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. COMS30014).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the Faculty workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an
assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.