| Unit name | Agent-Based Modelling |
|---|---|
| Unit code | SEMT30009 |
| Credit points | 20 |
| Level of study | H/6 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Professor. Richards |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) | |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | School of Engineering Mathematics and Technology |
| Faculty | Faculty of Engineering |
Why is this unit important?
Agent-based modelling involves constructing and experimenting with computer simulations of actions and interactions between individual members in populations of simulated ‘agents’, where each agent might represent a single person in some social setting, or a single company in an economy, or a single cell in an organism, or a single animal in an ecosystem, or a particular jet in an air transport network, or a non-player character in a CGI animation or a computer game, and so on. Typically the agents’ individual behaviours, and the interactions between the agents and their environment (which will often include other agents to interact with) are nonlinear and heterogeneous -- that is, the agents differ in their behaviours and responses. Very often the overall system, the nonlinearly interacting heterogeneous set of agents and the environment they are embedded within, exhibits “emergent behaviour”, i.e. behaviour that is difficult or impossible to predict in advance, even when given complete information about how each agent acts and interacts and all the nonlinearities in the system. Agent-based modelling is used increasingly in a wide range of application areas, because it can often provide insights into real-world systems that are too complex and varied to be tackled by traditional mathematical analysis and modelling methods.
How does this unit fit into your programme of study
This unit gives students a thorough grounding in foundational agent-based models, and then further develops this by discussion and analysis of notable and recently-published peer-reviewed research publications that use agent-based models to make new contributions to knowledge.
An overview of content
Topics covered in this unit will include:
How will students, personally, be different as a result of the unit
Throughout this unit there is a focus on students developing their skills in agent-based modelling by studying previously successful ABM systems; on completion of this unit students will be better equipped to create their own ABMs of real-world systems either starting “from scratch” or by extending and refining pre-existing models.
Learning outcomes
On successful completion of this unit, students will be able to:
Teaching will be delivered through a combination of synchronous and asynchronous sessions, including pre-recorded video lectures, on-campus lecture/seminar/Q&A sessions, and formative self-directed exercises. The unit will be supported by regular computer labs; these will provide student-centred on-campus learning through practical problem solving and will create a supportive environment where students learn to independently apply the tools and techniques explored in the unit. Students will be expected to actively participate in the lectures, seminars, and labs and to engage with videos, readings, self-directed exercises, and problem-solving activities.
Tasks which help you learn and prepare you for summative tasks (formative):
Regular case-studies and computer laboratory exercises in which you will describe pre-existing agent-based models, create your own agent-based models, alter and extend existing agent-based models, generate and analyse results from agent-based models, and draw appropriate conclusions from your analysis. These exercises will include opportunities to get feedback on your work as well as developing your skills.
Tasks which count towards your unit mark (summative):
This unit is assessed by a coursework in the form of an individual report supported by a video (100%) assessing all learning outcomes.
When assessment does not go to plan:
Re-assessment takes the same form as the original summative assessment.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. SEMT30009).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The assessment methods listed in this unit specification are designed to enable students to demonstrate the named learning outcomes (LOs). Where a disability prevents a student from undertaking a specific method of assessment, schools will make reasonable adjustments to support a student to demonstrate the LO by an alternative method or with additional resources.
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
