This is an advanced undergraduate course that offers students the opportunity to study a special thematic area within the discipline of Artificial Intelligence.

The topics will vary from year to year in response to emerging theoretical and practical issues in the discipline, as well as the research interests and expertise of academics and sessional staff. They will be drawn from the broad areas of Artificial Intelligence, and could include (but not limited to) the following topics: Planning, Scheduling, Games, Search, Reasoning (constraint-based, model-based, spatial, temporal), Knowledge representation, Decision-making under uncertainty, Integrated planning and learning, Reinforcement learning, and Robotics.

Please see the class website for the specific topics covered in a particular semester.

Learning Outcomes

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

1. Gain both a wide and a deep knowledge of the topic(s) taught in the current instance of the course.
2. Navigate through, and critically examine the scientific literature on the taught topic(s).
3. Plan and execute project work and/or a piece of research and scholarship in the advanced topic(s)

Research-Led Teaching

This class will cover the basics and recent research results on the challenge of building AI systems that can act autonomously in the real physical world.

Recommended Resources

Whether you are on campus or studying online, there are a variety of online platforms you will use to participate in your study program. These could include videos for lectures and other instruction, two-way video conferencing for interactive learning, email and other messaging tools for communication, interactive web apps for formative and collaborative activities, print and/or photo/scan for handwritten work and drawings, and home-based assessment.

ANU outlines recommended student system requirements to ensure you are able to participate fully in your learning. Other information is also available about the various Learning Platforms you may use.

Staff Feedback

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

• written comments
• verbal comments
• feedback to whole class, groups, individuals, focus group etc

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). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Other Information

Gen AI Tools are ALLOWED:

 “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 convener for this course.”

Class Schedule

Week/Session	Summary of Activities	Assessment
1	Introduction to Physical AI systems (Weeks 1-2)	Labs are held for the students who have enrolled in those particular classes. Please only attend the lab you enrolled in. Drop-ins are open to the entire course cohort.
2	Foundations of Physical AI systems (~Weeks 3-7)	Student presentations and evaluations, paper reviews
3	Towards Physical AI systems (~Weeks 8-10)	Student presentations and evaluations, paper reviews
4	State of the Art Implementations of Physical AI systems (~Weeks 11-12)	Student presentations and evaluations, paper reviews

Tutorial Registration

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

Assessment Summary

Assessment task	Value	Learning Outcomes
Assignment 1 - Paper presentation - Individual Assignment	20 %	1,2
Assignment 2 - Paper reviews A, B, C - Individual Assignment	15 %	1,2
Assignment 3 - Evaluation - Individual Assignment	15 %	1,2
Assignment 4 - Team project	50 %	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 Integrity Rule before the commencement of their course. Other key policies and guidelines include:

• Academic Integrity Policy and Procedure
• Student Assessment (Coursework) Policy and Procedure
• Extenuating Circumstances Application
• Student Surveys and Evaluations
• Deferred Examinations
• Student Complaint Resolution Policy and Procedure
• Code of practice for teaching and learning

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 Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

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

Students are strongly encouraged to attend all classes and tutorials. This course has been designed for students to benefit from vicarious learning which is a pedagogically strong approach to student learning where students learn from hearing about experiences of others during Q&As, through casual peer conversations during class and sharing experiences.

Attendance is required as a bare minimum for:

• the class where the student is presenting (assignment 1)
• the classes where the student is reviewing a paper (assignment 2)
• Assignment 3 completion (students can opt out of this assignment if they cannot attend classes)

At least one student per team is required to attend the weekly tutorial and present their progress. Students may be randomly selected to present their team's work.

Assessment Task 1

Assignment 1 - Paper presentation - Individual Assignment

In weeks 1 and 2, students are required to select a topic/paper from a given list of topics/papers and have to give a presentation about this in class at a predefined date and time in weeks 3-12 and answer audience questions.

Assessment Task 2

Assignment 2 - Paper reviews A, B, C - Individual Assignment

Students have to select one paper for each of the three parts of the course (weeks 3-6, 7-9, 10-12), write a review about the paper and contribute to the discussion of the paper.

This assignment consists of 3 parts, one for each part of the course with varying deadlines.

Assessment Task 3

Assignment 3 - Evaluation - Individual Assignment

Students have to evaluate presentations and discussions by other students over 10 weeks and answer quizzes. One evaluation per week.

Assessment Task 4

Assignment 4 - Team project

For the team project, students select an existing simulator of a physical environment and identify/develop/train a baseline AI agent that can perform well in the simulator. Students then introduce novelties to the environment similar to what could happen in the real world and evaluate the performance of their baseline agent using the open world learning evaluation protocol. Finally, they retrain/adjust their baseline agent to the novelties and reevaluate it.

Each of the tasks is staged, with individual milestones due approximately every two weeks and a final report at the end of the semester.

Except for the final report, individual milestones may be marked during the tutorials.

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.

 

The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin. Programming assignments will be done via gitlab.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

Individual assessment tasks may or may not allow for late submission. Policy regarding late submission is detailed below:

• Late submission not permitted. If submission of assessment tasks without an extension after the due date is not permitted, a mark of 0 will be awarded.
• Late submission permitted. Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted 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.

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).

• ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
• ANU Access and inclusion for students with a disability or ongoing or chronic illness
• ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
• ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
• ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
• ANUSA supports and represents all ANU students