ARTIFICIAL INTELLIGENCE: LOGIC AND REASONING
CSE5ALR
2020
Credit points: 15
Subject outline
In this subject, you will learn the theories and methodologies of Automated Reasoning (i.e. reasoning conducted by a computer). Topics covered include first order and higher order logic, semantics-based and syntax-based reasoning methodologies, planning and robotics, semantic web and ontology, and cognitive computing. You will also learn to program in PROLOG which is an important Artificial Intelligence (AI) programming language.
School: Engineering and Mathematical Sciences (Pre 2022)
Credit points: 15
Subject Co-ordinator: Fei Liu
Available to Study Abroad/Exchange Students: Yes
Subject year level: Year Level 5 - Masters
Available as Elective: No
Learning Activities: N/A
Capstone subject: No
Subject particulars
Subject rules
Prerequisites: CSE1PE OR CSE4IP
Co-requisites: N/A
Incompatible subjects: N/A
Equivalent subjects: N/A
Quota Management Strategy: N/A
Quota-conditions or rules: N/A
Special conditions: N/A
Minimum credit point requirement: N/A
Assumed knowledge: N/A
Learning resources
Artificial intelligence: structures and strategies for complex problem solving.
Resource Type: Book
Resource Requirement: Prescribed
Author: Luger, G.
Year: 2009
Edition/Volume: 6TH EDN
Publisher: ADDISON WESLEY
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
PROLOG: Programming for Artificial Intelligence
Resource Type: Book
Resource Requirement: Recommended
Author: Bratko, I.
Year: 2012
Edition/Volume: 6TH EDN
Publisher: ADDISON WESLEY
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Artificial intelligence: A modern approach.
Resource Type: Book
Resource Requirement: Recommended
Author: Russel, S. and Norvig, P.
Year: 2016
Edition/Volume: 3RD EDN
Publisher: PRENTICE- HALL
ISBN: N/A
Chapter/article title: N/A
Chapter/issue: N/A
URL: N/A
Other description: N/A
Source location: N/A
Career Ready
Career-focused: No
Work-based learning: No
Self sourced or Uni sourced: N/A
Entire subject or partial subject: N/A
Total hours/days required: N/A
Location of WBL activity (region): N/A
WBL addtional requirements: N/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Melbourne (Bundoora), 2020, Semester 1, Day
Overview
Online enrolment: No
Maximum enrolment size: N/A
Subject Instance Co-ordinator: Fei Liu
Class requirements
Computer LaboratoryWeek: 11 - 22
One 2.00 hours computer laboratory per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.
LectureWeek: 10 - 22
One 2.00 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Assessments
| Assessment element | Category | Contribution | Hurdle | % | ILO* |
|---|---|---|---|---|---|
One Programming Assignment (equivalent to 3000 words)An assignment on automated reasoning | N/A | N/A | No | 50 | SILO2 |
One 2-hour Examination (2000 words equivalent) | N/A | N/A | No | 50 | SILO1, SILO2, SILO3, SILO4 |