FIT5222 · Planning and automated reasoning

Overview

This unit focuses on the foundations of automated planning and reasoning and their real-world applications. Autonomous agents are active agents that independently execute actions to achieve a certain goal or goals. These agents perceive their environment and reason and plan in order to effect their environment and achieve their goals. This is a very popular and highly researched AI approach and has many significant implications beyond the traditional area of AI (optimisation, robotics, scheduling, etc?). This course will give you the foundations to develop and design your own autonomous agents.

Offerings

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. explain the theoretical concepts of automated planning and reasoning techniques;
2. apply agent modelling techniques to analyse, design and implement a small agent-based system;
3. evaluate, design, and implement automated planning and reasoning technique;
4. describe strengths and weaknesses of different automated planning and reasoning approaches for software agents;
5. apply automated planning and concurrent programming techniques to non-trivial distributed problems;
6. describe and discuss planning security challenges and solutions through goal recognition algorithms.

Workload

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.

Student experience, not official rules. Nothing here changes what the Handbook says.