Module ICP-2025:
AI for Games

Module Facts

Run by School of Computer Science and Electronic Engineering

10 Credits or 5 ECTS Credits

Semester 1

Organiser: Dr Llyr Ap Cenydd

Overall aims and purpose

• To present artificial intelligence (A.I.) – fundamental concepts, theories, tools and technologies – in the applied setting of constructing computer games.

Course content

• Introduction to Artificial Intelligence technologies and how they can be used to construct computer games.

• Introduction to the core topic of the application of AI algorithms and approaches in modern computer games.

• Introduction to the appropriate game enabling technologies for designing movement, animation and behaviour for games.

• Introduce how search algorithm can be applied within a game context.

• Artificial Life agents for games

• Discussion over professional, moral and ethical issues of A.I.

Learning outcomes mapped to assessment criteria

  threshold

40%

good

60%

excellent

70%

Explain how artificial intelligent technologies can be applied to construct computer games.

Has a basic knowledge of most of the course material and can analyse and design familiar systems. Understands basic concepts of machine ethics. Can build basic computer game AI. Can author a basic blog outlining game development. Has an excellent understanding of the course material and an ability to analyse and design to a high standard. Can build a non-trivial computer game employing A.I. technologies such as searching, procedural generation and evolutionary computing. Can write an outstanding video blog for the game. Can write an in-depth blog that clearly outlines development and demonstrates great understanding of application of AI in games. Understands most of the course material and can analyse and design most unfamiliar systems. Can build non-trivial computer game AI. Can author a moderate blog for the game including several applications of AI.

Demonstrate how to use a programming language to design AI algorithms and build games using a game engine.

Able to produce basic AI algorithms using engines such as Unity and NetLogo, including simple behaviours like seek and flee. Able to use engine tools to create a basic game. Able to implement AI algorithms in engines like Unity and Netlogo such as steering behaviours and searching algorithms. Can write complex AI algorithms in Java, C++, C#, Python or Javascript and/or use engines like Unity and NetLogo to produce complex AI algorithms like procedural generators, learning systems and genetic algorithms.

Explain the concepts of behaviour-based AI and how they are relevant for designing computer games.

Can explain in detail the advantages and disadvantages of different behaviour-based AI approaches and know when to apply them. Has an understanding of the current state of the art in behaviour-based AI. Can explain the idea behind concepts like Breitenberg Vehicles, Finite State Machines and Steering Behaviours. Can display a basic understanding of AI concepts like steering behaviours and reactionary AI algorithms.

Demonstrate an understanding of current research in the field of AI in games.

Has basic knowledge of trends in AI research and industry, including disruptive new technologies like AR and VR. Able to cite examples of AI research applicable to games such as machine learning, virtual reality and procedural animation. Able to discuss state of the art AI research from both industry and literature. Can write at length about emerging AI technologies and algorithms.

Apply various A.I. related search strategies and apply them to the design of computer games.

Can compare different search, neighbourhood and path finding strategies for appropriate tasks. Capable of implementing search strategies through code. Has expert knowledge of AI search strategies and path finding. Can program various searching algorithms from scratch, including optimisation. Has a basic understanding of search strategies like depth first and breadth first search. Can use engines like Unity and NetLogo to perform search tasks like path finding.

Explain about a selection of A.I. and Artificial Life techniques useful for implementing computer games.

Has a basic understanding of AI and A-Life techniques. Can explain in detail the idea behind AI and A-Life techniques. Can explain concepts such as self-organisation and emergent behaviour, and how it manifests in boid and swarm algorithms. Has an excellent understanding of all AI and A-Life techniques covered in the module and can explain the theory behind each in detail.

Describe concerns over professional, moral and ethical issues over exploiting A.I. in games.

Has an excellent understanding of contemporary and potential future issues around AI development and new technologies, for example online AI, Artificial Life and VR Avatars. Has a basic understanding of the issues surrounding exploiting AI in games. Can give examples and discuss issues surrounding professional, moral and ethical issues relevant to AI.

Assessment Methods

Type Name Description Weight
Examination 30
Game Code Report 70

Teaching and Learning Strategy

Hours
Lecture

12 hours over 12 weeks

12
 

ASSESSED assignments, including tutorial questions, problems, essays etc.

40
Laboratory

24 hours over 12 weeks

24
Private study 24

Transferable skills

  • Literacy - Proficiency in reading and writing through a variety of media
  • Numeracy - Proficiency in using numbers at appropriate levels of accuracy
  • Computer Literacy - Proficiency in using a varied range of computer software
  • Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
  • Exploring - Able to investigate, research and consider alternatives
  • Information retrieval - Able to access different and multiple sources of information
  • Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.
  • Safety-Consciousness - Having an awareness of your immediate environment, and confidence in adhering to health and safety regulations
  • Argument - Able to put forward, debate and justify an opinion or a course of action, with an individual or in a wider group setting
  • Self-awareness & Reflectivity - Having an awareness of your own strengths, weaknesses, aims and objectives. Able to regularly review, evaluate and reflect upon the performance of yourself and others

Subject specific skills

  • Knowledge and understanding of facts, concepts, principles & theories
  • Use of such knowledge in modelling and design
  • Problem solving strategies
  • Deploy theory in design, implementation and evaluation of systems
  • Recognise legal, social, ethical & professional issues
  • Specify, design or construct computer-based systems
  • Evaluate systems in terms of quality and trade-offs
  • Development of general transferable skills
  • Methods, techniques and tools for information modelling, management and security
  • Defining problems, managing design process and evaluating outcomes
  • Knowledge and understanding of mathematical principles
  • Knowledge and understanding of computational modelling
  • Principles of appropriate supporting engineering and scientific disciplines

Pre- and Co-requisite Modules

Courses including this module