• Class Number 4183
  • Term Code 3430
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
  • COURSE CONVENER
    • Prof Jochen Renz
  • LECTURER
    • Prof Jochen Renz
    • Dr Peng Zhang
  • Class Dates
  • Class Start Date 19/02/2024
  • Class End Date 24/05/2024
  • Census Date 05/04/2024
  • Last Date to Enrol 26/02/2024
  • TUTOR
    • Cheng Xue
    • Mary Kwan
    • Simon Brown
    • Amelia Genova
    • Harrison Bailey
    • Jiawen Wang
    • Oscar Czernuszyn
    • Yuxin Cao
SELT Survey Results

Artificial intelligence is the science that studies and develops methods of making computers more /intelligent/. The focus of this course is on core AI techniques for search, knowledge representation and reasoning, planning, and designing intelligent agents. The course also aims to give an overview of the historical, philosophical, and logical foundations of AI.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

After completing this course, students should be able to:
  1. Identify problems that are amenable to solution by AI methods, and which AI methods may be suited to solving a given problem.
  2. Formalise a given problem in the language/framework of different AI methods (e.g., as a search problem, as a constraint satisfaction problem, as a planning problem, etc).
  3. Implement basic AI algorithms (e.g., standard search or constraint propagation algorithms).
  4. Design and perform an empirical evaluation of different algorithms on a problem formalisation, and state the conclusions that the evaluation supports.

Examination Material or equipment

The exam will be in person and open book.

Course textbook is ”Artificial Intelligence - A Modern Approach”, by Stuart Russell and Peter Norvig (Prentice Hall 4th Edition, or Pearson Edition). This book gives a comprehensive tour of AI, and only a subset of it is part of the course material.

Staff Feedback

Students will be given feedback in the following forms in this course:

  • Written comments
  • Verbal comments
  • Feedback to the whole class, to groups, to individuals, focus groups

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.

Other Information

Academic honesty and plagiarism

Academic misconduct can seriously jeopardize your academic career, your future, and, if you are an international student, your ability to stay in Australia to study. It is the responsibility of each individual student to ensure that:

  • they are familiar with the expectations for academic honesty, both in general and in the specific context of particular disciplines or courses
  • work submitted for assessment is genuine and original
  • appropriate acknowledgement and citation is given to the work of others
  • they do not knowingly assist other students in academically dishonest practice.

Generally, it is fine to discuss the assignments with other students and to share ideas and information. However, when it comes to writing the actual material to be handed in for assessment, sit down and do the job by yourself. Hand in your own work, not somebody else’s, and all will be well. When in doubt about anything, ASK . . . and . . . ask EARLY—don’t leave it until the assignment due date. Your lecturers, tutors and College administrative staff are here to help you. It is the responsibility of everyone at the ANU to uphold and promote fundamental principles of quality and integrity in scholarly work.

Academic Skills and Learning Centre

http://www.anu.edu.au/students/contacts/academic-skills-learning-centre

The Academic Skills and Learning Centre (ASLC) offers ANU students free and confidential help with their academic work through individual consultations, workshops, courses, podcasts and handouts. Our aim is to assist students to develop the academic, critical thinking and communication strategies that are foundational to all scholarly activity. For ANU students, the ASLC offers:

  • individual consultations • workshops and courses
  • online and print materials and publications
  • the Language Exchange Program
  • podcasts
  • the Essay and Report Writing File

The ASLC is located on Level 2 of the John Yencken Building (Building 45) and is only closed on weekends and public holidays. 

Appeals Procedure

If you believe you have received an inappropriate or incorrect result, there are steps you can take to have that result reviewed. This must be done within 30 working days of the formal notification of results. Your first point of contact should be your tutor or the course convenor. 


The use of Generative AI Tools (e.g., ChatGPT) is permitted in this course, given that proper citation and prompts are provided, along with a description of how the tool contributed to the assignment. Guidelines regarding appropriate citation and use can be found on the ANU library website (https://libguides.anu.edu.au/generative-ai ). Marks will reflect the contribution of the student rather than the contribution of the tools. Further guidance on appropriate use should be directed to the course convener.

Class Schedule

Week/Session Summary of Activities Assessment
1 Foundations and History of AI, Intelligent Agents
2 Search Problems, Uninformed Search
3 Informed Search, Heuristics, Adversarial Search
4 Adversarial Search, Stochastic Games
5 Logical Agents, SAT
6 Constraint Satisfaction Problems, Inference, AC3
7 Local Search and optimal search for CSPs, Temporal Constraint Networks
8 Introduction to Planning, Classical Planning Representations
9 Planning Graph, Graphplan, Planning via Satisfiability
10 State Space Planning, Planning Heuristics, Partial-Order Planning
11 Guest Lectures. Each semester the course hosts one or two guest lectures, presenting on a range of subjects.
12 Examination Period Final exam

Assessment Summary

Assessment task Value Learning Outcomes
Mini Quizzes 10 % 1, 2, 3
Search Assignment 5 % 2, 3, 4
KRR Assignment 5 % 2, 3, 4
Planning Assignment 5 % 2, 3, 4
Search test 10 % 1, 2, 3
KRR test 10 % 1, 2, 3
Planning Test 10 % 1, 2, 3
Final exam 45 % 1, 2, 3

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website Students may choose not to submit assessment items through Turnitin. In this instance you will be required to submit, alongside the assessment item itself, hard copies of all references included in the assessment item.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Participation

Assessment Task 1

Value: 10 %
Learning Outcomes: 1, 2, 3

Mini Quizzes

There will be 1 mini quiz after every class, starting week 2. The total mini quiz grade (0 to 100) is the sum of normalized mini quiz grades (that is, each mini quiz is in the 0 to 100 scale) divided by the number of mini quizzes

Assessment Task 2

Value: 5 %
Learning Outcomes: 2, 3, 4

Search Assignment

Programming tasks in Python related to the first part of the course (Search)

Assessment Task 3

Value: 5 %
Learning Outcomes: 2, 3, 4

KRR Assignment

Programming tasks in Python related to the second part of the course (KRR)

Assessment Task 4

Value: 5 %
Learning Outcomes: 2, 3, 4

Planning Assignment

Programming tasks in Python related to the third part of the course (Planning)

Assessment Task 5

Value: 10 %
Learning Outcomes: 1, 2, 3

Search test

Short test at the end of the first part of the course (Search).

Assessment Task 6

Value: 10 %
Learning Outcomes: 1, 2, 3

KRR test

Short test at the end of the second part of the course (KRR).

Assessment Task 7

Value: 10 %
Learning Outcomes: 1, 2, 3

Planning Test

Short test at the end of the third part of the course (Planning).

Assessment Task 8

Value: 45 %
Learning Outcomes: 1, 2, 3

Final exam

Long examination at the end of the course during the exam period.

Academic Integrity

Academic integrity is a core part of our culture as a community of scholars. At its heart, academic integrity is about behaving ethically. This means that all members of the community commit to honest and responsible scholarly practice and to upholding these values with respect and fairness. The Australian National University commits to embedding the values of academic integrity in our teaching and learning. We ensure that all members of our community understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with. The University has policies and procedures in place to promote academic integrity and manage academic misconduct. Visit the following Academic honesty & plagiarism website for more information about academic integrity and what the ANU considers academic misconduct. The ANU offers a number of services to assist students with their assignments, examinations, and other learning activities. The Academic Skills and Learning Centre offers a number of workshops and seminars that you may find useful for your studies.

Online Submission

All assignments in this course are delivered via gitlab.

Hardcopy Submission

Late Submission

This course has a firm deadline policy. Assignments are submitted via gitlab, and you will be assessed based on the work submitted by the deadline. Late submissions are not accepted. In cases where students are unable to make a deadline (eg through illness or misadventure), they should use ANU's special assessment consideration mechanism to ensure that their circumstances are properly accommodated through alternative assessment.

Referencing Requirements

Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.

Returning Assignments

Assignments are marked promptly with feedback posted to gitlab. The quizzes can be reviewed including their feedback in wattle.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure The Course Convener may grant extensions for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Resubmission of Assignments

Assignments may not be resubmitted.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information. In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service — including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy. If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes. Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).
Prof Jochen Renz
51767
u4324570@anu.edu.au

Research Interests


Artificial Intelligence, knowledge representation, spatial reasoning, temporal reasoning, qualitative reasoning, constraint satisfaction, efficient algorithms, computational complexity, scheduling, operations research, cognitive science, spatial information systems, wireless sensor networks, navigation, trust and reputation, useful games

Prof Jochen Renz

By Appointment
Sunday
Prof Jochen Renz
51767
jochen.renz@anu.edu.au

Research Interests


Prof Jochen Renz

By Appointment
Sunday
Dr Peng Zhang
51767
p.zhang@anu.edu.au

Research Interests


Artificial Intelligence, knowledge representation, spatial reasoning, temporal reasoning, qualitative reasoning, constraint satisfaction, efficient algorithms, computational complexity, scheduling, operations research, cognitive science, spatial information systems, wireless sensor networks, navigation, trust and reputation, useful games

Dr Peng Zhang

Sunday
Cheng Xue
cheng.xue@anu.edu.au

Research Interests


Cheng Xue

Sunday
Mary Kwan
51767
heitung.kwan@anu.edu.au

Research Interests


Artificial Intelligence, knowledge representation, spatial reasoning, temporal reasoning, qualitative reasoning, constraint satisfaction, efficient algorithms, computational complexity, scheduling, operations research, cognitive science, spatial information systems, wireless sensor networks, navigation, trust and reputation, useful games

Mary Kwan

Sunday
Simon Brown
51767
simon.brown@anu.edu.au

Research Interests


Artificial Intelligence, knowledge representation, spatial reasoning, temporal reasoning, qualitative reasoning, constraint satisfaction, efficient algorithms, computational complexity, scheduling, operations research, cognitive science, spatial information systems, wireless sensor networks, navigation, trust and reputation, useful games

Simon Brown

Sunday
Amelia Genova
51767
u4324570@anu.edu.au

Research Interests


Artificial Intelligence, knowledge representation, spatial reasoning, temporal reasoning, qualitative reasoning, constraint satisfaction, efficient algorithms, computational complexity, scheduling, operations research, cognitive science, spatial information systems, wireless sensor networks, navigation, trust and reputation, useful games

Amelia Genova

Sunday
Harrison Bailey
51767
u4324570@anu.edu.au

Research Interests


Artificial Intelligence, knowledge representation, spatial reasoning, temporal reasoning, qualitative reasoning, constraint satisfaction, efficient algorithms, computational complexity, scheduling, operations research, cognitive science, spatial information systems, wireless sensor networks, navigation, trust and reputation, useful games

Harrison Bailey

Sunday
Jiawen Wang
51767
u4324570@anu.edu.au

Research Interests


Artificial Intelligence, knowledge representation, spatial reasoning, temporal reasoning, qualitative reasoning, constraint satisfaction, efficient algorithms, computational complexity, scheduling, operations research, cognitive science, spatial information systems, wireless sensor networks, navigation, trust and reputation, useful games

Jiawen Wang

Sunday
Oscar Czernuszyn
51767
u4324570@anu.edu.au

Research Interests


Artificial Intelligence, knowledge representation, spatial reasoning, temporal reasoning, qualitative reasoning, constraint satisfaction, efficient algorithms, computational complexity, scheduling, operations research, cognitive science, spatial information systems, wireless sensor networks, navigation, trust and reputation, useful games

Oscar Czernuszyn

Sunday
Yuxin Cao
51767
u4324570@anu.edu.au

Research Interests


Artificial Intelligence, knowledge representation, spatial reasoning, temporal reasoning, qualitative reasoning, constraint satisfaction, efficient algorithms, computational complexity, scheduling, operations research, cognitive science, spatial information systems, wireless sensor networks, navigation, trust and reputation, useful games

Yuxin Cao

Sunday

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions