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Module ICE-2701:
AI & Game Design

Module Facts

Run by School of Computer Science and Electronic Engineering

20 Credits or 10 ECTS Credits

Semester 2

Organiser: Dr Llyr Ap Cenydd

Overall aims and purpose

To present artificial intelligence (AI) – fundamental concepts, theories, tools and technologies – in the applied setting of developing computer games.

Course content

Indicative content includes:

  • Introduction to Artificial Intelligence (AI) 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 algorithms can be applied within a game context.
  • Introduce Artificial Life concepts and their application in games.
  • Provide practical experience of developing AI agents and techniques in a game engine.

Assessment Criteria

excellent

Equivalent to the range 70%+. Assemble critically evaluated, relevent areas of knowledge and theory to constuct professional-level solutions to tasks and questions presented. Is able to cross-link themes and aspects to draw considered conclusions. Presents outputs in a cohesive, accurate, and efficient manner.

good

Equivalent to the range 60%-69%. Is able to analyse a task or problem to decide which aspects of theory and knowledge to apply. Solutions are of a workable quality, demonstrating understanding of underlying principles. Major themes can be linked appropriately but may not be able to extend this to individual aspects. Outputs are readily understood, with an appropriate structure but may lack sophistication.

threshold

Equivalent to 40%. Uses key areas of theory or knowledge to meet the Learning Outcomes of the module. Is able to formulate an appropriate solution to accurately solve tasks and questions. Can identify individual aspects, but lacks an awareness of links between them and the wider contexts. Outputs can be understood, but lack structure and/or coherence.

Learning outcomes

  1. Discuss the state of the art and future of AI in games.

  2. Demonstrate various search and navigation strategies and apply them in developing computer games.

  3. Implement AI algorithms and build games using a game engine.

  4. Describe concerns over professional, moral and ethical issues over exploiting AI in games.

  5. Explain the concepts of artificial life, intelligent agents and behaviour-based AI, and how they can be applied when designing video games.

  6. Explain various AI technologies and how they can be applied to construct computer games.

Assessment Methods

Type Name Description Weight
EXAM Examination

Exam

30
COURSEWORK Developed Game + Code

Develop a video game demonstrating various AI techniques in Unity.

40
INDIVIDUAL BLOG Development Blog

Blog detailing game development and short article.

30

Teaching and Learning Strategy

Hours
Lecture

12 hours over 12 weeks

12
Laboratory

2 hours per week for 12 weeks

24
Private study

Background reading, revision, game engine tutorials.

68
Individual Project

Semester wide assignment and report

96

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
  • Presentation - Able to clearly present information and explanations to an audience. Through the written or oral mode of communication accurately and concisely.
  • 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

Courses including this module