ARTIFICIAL INTELLIGENCE: LOGIC & REASONING

CSE4ALR

Not currently offered

Credit points: 15

Subject outline

In this subject, students are provided with the opportunity to study some major research areas of Artificial Intelligence. Topics includes PROLOG Programming, Logic Programming, Stream Reasoning, Natural Language Processing, Planning, Semantic Web and Sentiment Analysis.

SchoolSchool Engineering&Mathematical Sciences

Credit points15

Subject Co-ordinatorFei Liu

Available to Study Abroad StudentsYes

Subject year levelYear Level 4 - UG/Hons/1st Yr PG

Exchange StudentsYes

Subject particulars

Subject rules

Prerequisites CSE1IOO or CSE4IOO

Co-requisitesN/A

Incompatible subjects CSE3ALR

Equivalent subjectsN/A

Special conditionsN/A

Learning resources

Readings

Resource TypeTitleResource RequirementAuthor and YearPublisher
ReadingsArtificial Intelligence (6th ed)PrescribedLuger G. and 2009Addison-Wesley

Graduate capabilities & intended learning outcomes

01. Apply the knowledge in automated reasoning to analyse and evaluate a reasoning resolution in order to select a proper reasoning resolution to design and implement an static/dynamic intelligent computer system.

Activities:
In lectures, students learn formal language and formal system; understand first order logic as a formal system; study SLD-resolution (substitution, unification, SLD-derivation, selection rule, ordering rule and computation rule); understand soundness and completeness and learn stream-based real-time reasoning. Students learn the contents by listening to the lecture, participating in class discussion, doing the class exercises and completing the lab questions.
Related graduate capabilities and elements:
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Discipline -Specific Knowledge and Skills (Discipline-Specific Knowledge and Skills)

02. Apply the sentence parsing techniques in natural language analysis and evaluation in order to select a parsing technique and implement a computer system to analyse different components of a sentence for the purpose of linguistic analysis and language translation

Activities:
In lectures, students study Specification and Parsing Using Context-Free Grammars and apply it in sentence parsing and decomposition. Students learn the contents by listening to the lecture, participating in class discussion, doing the class exercises and completing the lab questions.
Related graduate capabilities and elements:
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Discipline -Specific Knowledge and Skills (Discipline-Specific Knowledge and Skills)

03. Design, code and evaluate an AI system being implemented in PROLOG.

Activities:
In lectures, students learn PROLOG program design and programming skills such as recursion, iteration, selection, file operations, list operations, structures and pre-defined predicates. Students learn the contents by listening to the lecture, participating in class discussion, doing the class exercises and completing the lab questions. The examination tests the knowledge through short question-answer and PROLOG programming questions.
Related graduate capabilities and elements:
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Discipline -Specific Knowledge and Skills (Discipline-Specific Knowledge and Skills)

04. Design and implement programs to analyse the sentiment orientation of a text document.

Activities:
In lectures, students learn various techniques in text based sentiment analysis. These include the clustering based method, supervised method, unsupervised method and statistics based methods. Students learn the contents by reading relevant research papers and participating in class discussions.
Related graduate capabilities and elements:
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Inquiry and Analytical Skills (Critical Thinking,Creative Problem-solving,Inquiry/Research)
Discipline -Specific Knowledge and Skills (Discipline-Specific Knowledge and Skills)

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