FIT3203 Embodied artificial intelligence
Faculty of Information Technology
FIT3203 Embodied artificial intelligence is a level 3, 6-credit-point, undergraduate unit from the Faculty of Information Technology, offered in 2027 in Semester 2 at Clayton and Malaysia. It needs FIT2111 and (FIT2004 or FIT3234).
- Credit points
- 6
- Offered in 2027
- Semester 2
- Clayton, Malaysia
- Assessment
- No exam
- 3 tasks
- Workload
- 144 hours
- per semester
Reviews
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Requisites
Before FIT3203
Prerequisites
Pass these before you enrol.
After FIT3203
No unit lists FIT3203 as a prerequisite in the 2027 handbook.
Overview
Intelligence becomes more complex when artificial intelligence systems must perceive, move and act in the world. This unit explores embodied intelligence through the design of artificial intelligence systems for robots and physically situated agents, where sensing, perception, planning, learning and action must work together in dynamic environments.
You will examine how embodied agents use sensors to interpret their surroundings, build representations of the world, plan actions, adapt behaviour and pursue goals under uncertainty. The unit introduces key approaches in robotic perception, sensor fusion, planning, reinforcement learning, learned policies, simulation and agent architectures. Building on prior deep learning capability, you will apply machine learning methods to perception and decision-making tasks, while also considering how embodied systems interact with people, places and physical constraints.
Offerings in 2027
| Teaching period | Campus | Mode |
|---|---|---|
| Second semester | Clayton | Flexible |
| Second semester | Malaysia | On campus |
Assessment
- Assessment Task 1: Reinforcement Learning AgentArtefact30%
- Assessment Task 2: Multi-Agent PathfindingArtefact20%
- Assessment Task 3: Game Theory and Agent Decision-MakingWritten50%
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Learning outcomes
When you finish this unit, you should be able to:
- 1
Design embodied intelligence systems that integrate sensors, perception, learned models, planning, action and environmental constraints to achieve defined goals.
- 2
Use robotics, simulation, perception, planning and embodied intelligence tools to develop and evaluate physically situated artificial intelligence systems.
- 3
Apply machine learning and deep learning methods to support perception, sensor interpretation, policy learning or adaptive behaviour in embodied artificial intelligence systems.
- 4
Formulate and solve complex embodied intelligence problems involving uncertainty, dynamic environments, physical constraints, agent goals and action selection.
- 5
Evaluate how embodied artificial intelligence systems can be designed and applied to support social good, including safety, accessibility, sustainability, human benefit and responsible interaction with people and environments.
Workload and teaching
- Workshops24 hours
- Applied sessions22 hours
- Teaching approachActive learning
- Teaching approachEnquiry-based learning
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled teaching activities.
Where it fits
FIT3203 is part of 1 area of study in the 2027 handbook.
Common questions
When is FIT3203 offered?
In 2027, FIT3203 runs in Semester 2 at Clayton and Malaysia.
How much work is FIT3203?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does FIT3203 have an exam?
No. FIT3203 has 3 assessment tasks and no exam.
Which majors and minors include FIT3203?
FIT3203 is part of Artificial intelligence algorithms and models.
More details
- Credit points
- 6
- Level
- 3
- Study level
- Undergraduate
- Faculty
- Faculty of Information Technology
- Type
- Coursework
- EFTSL
- 0.125
- Student contribution
- SCA Band 2
- Study abroad
- Available
- Handbook years
- 20262027