Dr. Sander C.J. Bakkes discusses the potential for algorithms to replace game designers and the importance of considering individual player experiences in game design. He highlights the effectiveness of AI in creating personalized gaming experiences that cater to individual preferences and identifies that while some repetitive tasks can be automated, human supervision will always be necessary. His research indicates that players consistently prefer personalized games over static ones, showing the significant impact of tailored content on player satisfaction.

1. Dr. Ing. Sander C.J. Bakkes
Lecturer in Game Technology
University of Amsterdam

3. Can we Replace the GameCan we Replace the Game
Designer with an Algorithm?Designer with an Algorithm?

4. Question #1Question #1
“Is it important to“Is it important to
consider theconsider the individualindividual
player?”player?”

5. Player ExperiencePlayer Experience

6. Player ExperiencePlayer Experience

7. Player ExperiencePlayer Experience

8. Player ExperiencePlayer Experience

9. Player ExperiencePlayer Experience

11. Types of Player ModellingTypes of Player Modelling
Bakkes, Spronck, and Van Lankveld (2012).Bakkes, Spronck, and Van Lankveld (2012). Player BehaviouralPlayer Behavioural
Modelling for Video GamesModelling for Video Games. Entertainment Computing,. Entertainment Computing,
3(3):71-79.3(3):71-79.

12. ““SoSo: We have AI that can: We have AI that can
learn things, and AI thatlearn things, and AI that
can model the humancan model the human
player; what shall we useplayer; what shall we use
this for?”this for?”

13. ““CreatingCreating personalisedpersonalised
experiences”experiences”

14. MotivationMotivation
((11) psychological foundation, () psychological foundation, (22) effect on) effect on
player satisfaction, (player satisfaction, (33) contribution to game) contribution to game
development practise, (development practise, (44) instrumental to) instrumental to
achieving industry ambitionsachieving industry ambitions

16. Targeted content injectionTargeted content injection

17. ResultsResults
((11) Approach learns appropriate) Approach learns appropriate
challenge level within ~30 secs.challenge level within ~30 secs.
((22) Game adaptations can made) Game adaptations can made
specifically to certain game contentspecifically to certain game content
((33) Human participants consistently) Human participants consistently
prefer the personalised game overprefer the personalised game over
an identical static game (~72%)an identical static game (~72%)
Published at IEEE GEM 2014, FDG 2014, PCG 2014Published at IEEE GEM 2014, FDG 2014, PCG 2014

18. WonderingWondering
......

19. Can we achieve the same resultsCan we achieve the same results
by only analysingby only analysing facialfacial
expressionsexpressions??

20. Can we achieve the same resultsCan we achieve the same results
by only analysingby only analysing facialfacial
expressionsexpressions??

22. Question #2Question #2
“Can game design be“Can game design be
wholly or partiallywholly or partially
automatedautomated?”?”

33. ““So: Can we Replace theSo: Can we Replace the
Designer with anDesigner with an
AlgorithmAlgorithm?”?”

34. ““NoNo: Our AI is nowhere: Our AI is nowhere
near good enough yet.”near good enough yet.”

35. ““NoNo: There will always be: There will always be
a need for humana need for human
supervision.”supervision.”

36. ““YesYes: Lots of repetitive: Lots of repetitive
and low skilled designand low skilled design
tasks will becometasks will become
automated.”automated.”

37. The end of this talk

38. http://sander.landofsand.com/
sanderbakkes@gmail.com