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Curricular information is subject to change
• Students should be able to understand the basic concepts and principles of artificial intelligence and its corresponding processing algorithms.
• Be able to analysis and design A* search algorithm in a graph or ANDOR graph.
• Be able to propose question-answering system by using resolution methods and tautology.
1-2 Introduction to Intelligent Information Processing and Artificial Intelligent
3-8 Intelligent Information Search Methodologies and Algorithms
9-13 Logical Reasoning: Rules and Applications
14-15 Introduction to Knowledge Engineering
|Student Effort Type||Hours|
Not applicable to this module.
|Description||Timing||Component Scale||% of Final Grade|
|Examination: Final exam||2 hour End of Trimester Exam||No||Alternative linear conversion grade scale 60% (Chinese modules)||No||
|Attendance: Tutorial questions and attendance||Throughout the Trimester||n/a||Alternative linear conversion grade scale 60% (Chinese modules)||No||
|Class Test: Quiz||Throughout the Trimester||n/a||Alternative linear conversion grade scale 60% (Chinese modules)||No||
|Remediation Type||Remediation Timing|
|In-Module Resit||Prior to relevant Programme Exam Board|
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
• Self-assessment activities
Not yet recorded.