GAIG Game AI Research Group @ QMUL

[Seminar] 'Investigating optimum game difficulty using AI' by Joe Cutting


  • Title: Investigating optimum game difficulty using AI
  • Speaker: Joe Cutting (University of York)
  • Time and date: 1pm to 2pm, March 8th, 2023 (Wednesday)
  • Room: Virtual (Zoom)

The Game AI Research Group is glad to announce a (virtual) talk by Joe Cutting on March 8th 2023 at 1 PM.


How does the difficulty of a game affect people’s enjoyment and engagement? Intrinsic motivation and flow theories posit the relationship between difficulty/skill and experience follows an inverted U shape, with the optimum level being when difficulty and skill are balanced. However, the evidence for this is mixed. To determine the optimum level of difficulty/skill we created a simple online tactical game using a variant of the Monte-Carlo Tree Search algorithm to precisely control the level of difficulty in relation to players’ level of skill. We then performed two studies (n=311 and 309) to determine which ratio of difficulty / skill produced the optimum levels of enjoyment and behavioural engagement. Both studies showed that although players noticed the difference in their performance due to varying difficulty / skill balance this did not affect their levels of enjoyment or engagement.


Joe Cutting is a lecturer in the department of Computer Science, University of York. He studied both cognitive and computer science at the University of Birmingham before a varied career which included working at the London Science Museum and starting his own digital agency to create serious games. He completed his PhD under the IGGI games programme at the University of York before joining the Computer Science department as a lecturer. His research looks at many aspects of digital games including difficulty, serious game design, game experience, mental health and financial wellbeing.

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