| CODE | ARI1248 | |||||||||
| TITLE | Foundations of AI Logic and Modelling | |||||||||
| 今日黑料 LEVEL | 02 - Years 2, 3 in Modular Undergraduate Course | |||||||||
| EQF/MQF LEVEL | 5 | |||||||||
| ECTS CREDITS | 5 | |||||||||
| DEPARTMENT | Artificial Intelligence | |||||||||
| DESCRIPTION | This study-unit introduces students to the logical and structural foundations of Artificial Intelligence. It equips them with the reasoning and modelling skills needed to understand how AI systems represent, manipulate, and reason about knowledge. Students will explore the essential building blocks of formal reasoning and algorithm design including logic, sets, relations, functions, and graphs, through an AI-oriented perspective. Emphasis is placed on understanding, interpreting, and constructing methods used in intelligent systems, from simple rule-based reasoning to the representation of knowledge and constraints in computational environments. The unit covers topics such as propositional and predicate logic, knowledge representation and reasoning in AI, sets and relations, basics of counting and number theory, graph and tree representations, and iteration and recursion in computational models. Students will also explore constraint modelling and applications of logic in intelligent systems such as planning, search, and decision-making. Each topic is illustrated through AI-relevant examples such as decision trees, search spaces, constraint networks, and logical inference in expert systems. The approach encourages students to appreciate how mathematical reasoning directly supports AI algorithms and intelligent behaviour. Study-Unit Aims: The aim of this study-unit is to provide students with a solid grounding in the logical and mathematical principles that underpin Artificial Intelligence. It seeks to develop an understanding of how problems can be represented and reasoned about formally through concepts such as logic, sets, relations, and graphs. By focusing on applied reasoning and problem-solving, the unit enables students to model data, relationships, and constraints in ways that are directly relevant to intelligent systems. It also aims to cultivate analytical thinking and problem-solving skills. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - Explain the fundamental role of logic, sets, relations, and graphs in the theoretical foundations of Artificial Intelligence. - Describe how formal reasoning supports key AI processes such as knowledge representation, inference, and search. - Recognise and distinguish between different types of logical systems (propositional and predicate logic) and their applications in modelling intelligent behaviour. - Interpret how mathematical structures such as relations, functions, and graphs are used to model data and problem domains in AI systems. - Demonstrate knowledge of how formal models contribute to the design and operation of intelligent algorithms and reasoning mechanisms 2. Skills: By the end of the study-unit the student will be able to: - Apply logical reasoning and formal modelling techniques to represent and solve structured problems in Artificial Intelligence. - Construct and manipulate logical expressions, sets, relations, and graph-based models to describe computational or real-world scenarios. - Analyse problem statements to determine appropriate formal methods for representation and reasoning. - Evaluate and justify their chosen modelling approach through clear explanation and reflective reasoning. |
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| STUDY-UNIT TYPE | Lecture, Independent Study, Project and Tutorial | |||||||||
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2026/7. It may be subject to change in subsequent years. |
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