AI Planning for Autonomy
Subject COMP90054 (2016)
Note: This is an archived Handbook entry from 2016.
Credit Points: | 12.5 | ||||||||||||
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Level: | 9 (Graduate/Postgraduate) | ||||||||||||
Dates & Locations: | This subject has the following teaching availabilities in 2016: Semester 2, Parkville - Taught on campus.
Timetable can be viewed here. For information about these dates, click here. | ||||||||||||
Time Commitment: | Contact Hours: 36 hours, comprising of two 1-hour lectures and one 1-hour workshop per week Total Time Commitment: 200 hours | ||||||||||||
Prerequisites: |
To enol in this subject, students must satisfy one of these conditions:
Subject Study Period Commencement: Credit Points: | ||||||||||||
Corequisites: | None | ||||||||||||
Recommended Background Knowledge: | None | ||||||||||||
Non Allowed Subjects: |
433-481 Agent Programming Languages | ||||||||||||
Core Participation Requirements: |
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry. It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability |
Subject Overview: |
AIMS The key focus of this subject is the foundations of automated planning and reasoning and their real-world applications. Automated planning is the AI approach to developing agents that make their own decisions and is becoming increasingly popular. 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). This subject shows how this work is relevant for many applications beyond the traditional area of artificial intelligence, such as resource scheduling, logistics, process management, service composition, intelligent sensing and robotics. The subject focuses on the foundations that enable agents to reason autonomously about goals, perception, actions and the knowledge of other agents during collaborative task execution. This subject is an elective subject in the Master of Science (Computer Science) and Master of Information Technology, in particular for the Distributed Computing and the Computing Specialisations. It can also be taken as an Advanced Elective subject in the Master of Engineering (Software).
INDICATIVE CONTENT Topics are drawn from the field of advanced artificial intelligence including
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Learning Outcomes: |
INTENDED LEARNING OUTCOMES (ILO) On completion of this subject the student is expected to:
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Assessment: |
Hurdle requirement: The examination is a hurdle and must be passed to pass the subject. |
Prescribed Texts: |
Hector Geffner and Blai Bonet, A Concise Introduction to Models and Methods for Automated Planning, Morgan & Claypool, 2013 |
Breadth Options: | This subject is not available as a breadth subject. |
Fees Information: | Subject EFTSL, Level, Discipline & Census Date |
Generic Skills: |
On completion of the subject the students should have the following skills:
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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 LMS 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.
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Related Course(s): |
Doctor of Philosophy - Engineering Master of Information Technology Master of Information Technology Master of Philosophy - Engineering Master of Science (Computer Science) |
Related Majors/Minors/Specialisations: |
B-ENG Software Engineering stream MIT Computing Specialisation MIT Distributed Computing Specialisation Master of Engineering (Software) |
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