The effects of AI Optimised Difficulty on gameplay experience

Research background

The purpose of this research project is to investigate how AI Optimised Difficulty affects gameplay experience in video games, the hypothesis being that it will positively affect gameplay experience. AI Optimised Difficulty is here defined as a form of DDA that uses AI to optimise game difficulty against various parameters of difficulty and of the player’s skill, ensuring that the difficulty level is optimised for the player.

We investigated game difficulty balance as well as gameplay experience and how to measure it.

Method and game

A game prototype implementing AI Optimised Difficulty was tested using a between groups design. Gameplay experience was measured using both subjective and objectives methods, i.e. self-report questionnaires and facial expression analysis, respectively. Thematic Analysis and video review sessions were also used. The test results were correlated, analysed and tested for statistical significance.

The game is a 2D shooter game. The objective is for the player to attempt to score as highly as possible. Score is affected by defeating enemies and by the player dying. If the player dies, they will respawn. The game is split into short segments, with each segment containing a few enemies. DDA is constantly calculated. After each death the player is restored to full health and respawned. Health is also slowly regained over time.

Conclusion

The results were deemed statistically not significant. However, they imply that the implementation of AI Optimised Difficulty improved the gameplay experience, thus supporting the hypothesis.

My contribution

Analysis, graphics, report writing, research, test setup and execution
We were a group of four people.