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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.
Week Topic
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
16 Revision
Student Effort Type | Hours |
---|---|
Lectures | 48 |
Total | 48 |
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 | 65 |
Attendance: Tutorial questions and attendance | Throughout the Trimester | n/a | Alternative linear conversion grade scale 60% (Chinese modules) | No | 15 |
Class Test: Quiz | Throughout the Trimester | n/a | Alternative linear conversion grade scale 60% (Chinese modules) | No | 20 |
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.