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Emerging and advanced topics in artificial intelligence
FIT3192
Synopsis
This advanced undergraduate unit delves into the forefront of Artificial Intelligence, offering you an in-depth exploration of emerging and cutting-edge topics within the field. The course is designed to keep pace with the rapid advancements in AI, providing a comprehensive understanding of both foundational and innovative concepts.
Key topics covered in this course include 1) Multi-Agent Systems - Study the dynamics of systems where multiple autonomous agents interact, cooperate, or compete to achieve individual or collective goals; 2) Quantum Machine Learning - Investigate the intersection of quantum computing and machine learning and its potential applications in optimisation, cryptography, and complex data analysis; 3) Cognitive Systems - Examine AI systems that simulate human cognitive processes, including perception, reasoning, learning, and decision-making; and 4) Integrated Planning and Learning: Explore methods that combine planning and learning to enable AI systems to adapt and optimise their strategies in real-time with applications such as robotics, autonomous systems, and complex decision-making scenarios.
You will have a robust understanding of these advanced AI topics and be equipped with the knowledge to contribute to the development and application of innovative AI solutions in various domains.
Sourced from the Monash Handbook 2026.
Quick facts
- Credit points
- 6
- Level
- 3
- Audience
- Undergraduate
- Type
- Coursework
- School
- Faculty of Information Technology
- Handbook year
- 2026
Prerequisites (2)
What it unlocks
Nothing in the visible graph depends on this unit.
Listed in 1 area of study
- Artificial intelligenceElective units