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AI Planning for Autonomy (COMP90054)
Graduate courseworkPoints: 12.5Dual-Delivery (Parkville)
From 2023 most subjects will be taught on campus only with flexible options limited to a select number of postgraduate programs and individual subjects.
To learn more, visit COVID-19 course and subject delivery.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 1
Tim Miller
Semester 2
Dr Nir Lipovetzky
Overview
Availability | Semester 1 - Dual-Delivery Semester 2 - Dual-Delivery |
---|---|
Fees | Look up fees |
AIMS
The key focus of this subject is the foundations of autonomous agents that reason about action, applying techniques such as automated planning, reinforcement learning, game theory, and their real-world applications. Autonomous agents are active entities that perceive their environment, reason, plan and execute appropriate actions to achieve their goals, in service of their users (the real world, human beings, or other agents). The subject focuses on the foundations that enable agents to reason autonomously about goals & rewards, perception, actions, strategy, and the knowledge of other agents during collaborative task execution, and the ethical impacts of agents with this ability.
The programming language used in this subject is Python. No lectures or workshops on Python will be delivered.
INDICATIVE CONTENT
Topics are drawn from the field of advanced artificial intelligence including:
- Search algorithms and heuristic functions
- Classical (AI) planning
- Markov Decision Processes
- Reinforcement learning
- Game theory
- Ethics in AI planning
Intended learning outcomes
On completion of this subject the student is expected to:
- Apply theoretical concepts of reasoning about actions to single and multi-agent problems
- Be able to analyse, design, and implement automated planning, reinforcement learning, and game theoretic techniques to given problems
- Understand the strengths, weaknesses, and ethical consequences of different approaches for reasoning about action
- Be able to critically evaluate and choose the right technique for different problems in reasoning about action
- Communicate technical solutions about automated planning, reinforcement learning, and game theory
Generic skills
On completion of the subject the students should have the following skills:
- Ability to undertake problem identification, formulation, and solution
- Ability to utilise a systems approach to complex problems and to design and operational performance
- Ability to manage information and documentation
- Capacity for creativity and innovation ability to communicate effectively with both the engineering team and the community at large
Last updated: 31 January 2024
Eligibility and requirements
Prerequisites
Students must meet one of the following prerequisite options:
Option 1
Admission into or selection of one of the following:
- MC-IT100 Master of Information Technology
- MC-SCICMP Master of Science (Computer Science)
- MC-CS Master of Computer Science
- MC-DATASC Master of Data Science
Option 2
Admission into the 150pt Program course entry point in the MC-IT Master of Information Technology
AND
Admission into or selection of one of the following:
- Artificial Intelligence specialisation (formal) in the MC-IT Master of Information Technology
- Computing specialisation (formal) in the MC-IT Master of Information Technology
- Cyber Security specialisation (formal) in the MC-IT Master of Information Technology
- Distributed Computing specialisation (formal) in the MC-IT Master of Information Technology
Option 3
One of
Code | Name | Teaching period | Credit Points |
---|---|---|---|
COMP20003 | Algorithms and Data Structures | Semester 2 (Dual-Delivery - Parkville) |
12.5 |
COMP20007 | Design of Algorithms | Semester 1 (Dual-Delivery - Parkville) |
12.5 |
COMP90038 | Algorithms and Complexity |
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
|
12.5 |
ENGR30003 | Numerical Programming for Engineers | No longer available | |
ENGR30004 | Numerical Algorithms in Engineering |
Semester 1 (Dual-Delivery - Parkville)
Semester 2 (Dual-Delivery - Parkville)
|
12.5 |
Corequisites
None
Non-allowed subjects
None
Recommended background knowledge
SWEN20003 Object Oriented Software Development or COMP90041 Programming and Software Development
Basic understanding of logic and set theory. Basic understanding of introductory probability theory.
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 31 January 2024
Assessment
Semester 1
Description | Timing | Percentage |
---|---|---|
One team-based project, involving 2 to 3 team members, requiring approximately 30 - 40 hours of work per student. ILOs 1 to 5 are addressed in this assignment.
| Week 11 | 30% |
One team-based video presentation of approximately 3-5 minutes duration, involving 2 to 3 team members, each member contributing approximately 6 hours of work. ILOs 1 and 5 are addressed in this team-based assignment.
| Week 12 | 5% |
Two individual programming assignments due in weeks 5 and 8, taking approximately 13-15 hours of work each. ILOs 1 and 2 are addressed in these assignments. Each assignment is worth 10%.
| From Week 5 to Week 8 | 20% |
A 20-minute online quiz in week 6. ILOs 1 to 3 are addressed in this quiz.
| Week 6 | 5% |
One written 2-hour closed book end-of-semester examination. ILOs 1, 3, 4, and 5 are addressed in the exam.
| End of semester | 40% |
Semester 2
Description | Timing | Percentage |
---|---|---|
Assignment 1 - Individual - 10% - due Week 4 (Friday). Intended Learning Outcomes (ILOs) 1 and 2 are addressed.
| Week 4 | 10% |
Assignment 2 - Individual - 5% - due Week 6 (Friday). Intended Learning Outcomes (ILOs) 1 and 2 are addressed.
| Week 6 | 5% |
Pre-competition - Group - 10% - due Week 9 (Friday). 15-20 hours of work per student. Intended Learning Outcomes (ILOs) 1 to 5 are addressed.
| Week 9 | 10% |
Assignment 3 - Group- 35% - due Week 12 (Friday). 40-45 hours of work per student . Intended Learning Outcomes (ILOs) 1 to 5 are addressed.
| Week 12 | 35% |
Closed Book Exam - 40% - exam period. Intended Learning Outcomes (ILOs) 1, 3, 4, and 5 are addressed in the exam.
| During the examination period | 40% |
Last updated: 31 January 2024
Dates & times
- Semester 1
Principal coordinator Timothy Miller Mode of delivery Dual-Delivery (Parkville) Contact hours 36 hours, comprising of two 1-hour lectures and one 1-hour tutorial per week Total time commitment 200 hours Teaching period 28 February 2022 to 29 May 2022 Last self-enrol date 11 March 2022 Census date 31 March 2022 Last date to withdraw without fail 6 May 2022 Assessment period ends 24 June 2022 Semester 1 contact information
Tim Miller
- Semester 2
Principal coordinator Nir Lipovetzky Mode of delivery Dual-Delivery (Parkville) Contact hours 36 hours, comprising of two 1-hour lectures and one 1-hour tutorial per week Total time commitment 200 hours Teaching period 25 July 2022 to 23 October 2022 Last self-enrol date 5 August 2022 Census date 31 August 2022 Last date to withdraw without fail 23 September 2022 Assessment period ends 18 November 2022 Semester 2 contact information
Dr Nir Lipovetzky
Time commitment details
200 hours
Last updated: 31 January 2024
Further information
- Texts
Prescribed texts
- Subject notes
LEARNING AND TEACHING METHODS
The subject involves two 1-hour lectures per week followed by a 1 one hour workshop held in a computer laboratory. Weekly readings are assigned from textbooks, and weekly laboratory exercises are assigned. A significant amount of project work is assigned.
INDICATIVE KEY LEARNING RESOURCES
At the beginning of the year, the coordinator will propose textbook(s) on computer graphics and interaction and will be made available through the University Book Shop and library. Students will have access to lecture notes and lecture slides. The subject CANVAS site also contains links to recommended literature and current survey papers of software agent principles.
CAREERS / INDUSTRY LINKS
The IT industry is a large and steadily growing industry and advanced artificial intelligence techniques such as software agents are increasingly an integral part of the many facets of this industry. The University of Melbourne and Microsoft have created a new teaching innovative, Apps@Melbourne, for the many talented students keen on developing Apps for tablet computers. Students enrolled in this subject have the opportunity to publish Apps they have developed on the store to be made available to the wider community.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Data Science Course Ph.D.- Engineering Course Doctor of Philosophy - Engineering Course Master of Science (Computer Science) Course Master of Philosophy - Engineering Specialisation (formal) Computing Specialisation (formal) Distributed Computing Specialisation (formal) Software Specialisation (formal) Mechatronics - Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Additional information for this subject
Subject coordinator approval required.
- Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 31 January 2024