21st Century Game Design (Game Development Series)
21st Century Game Design (Game Development Series)
A Theory of Fun for Game Design
A Theory of Fun for Game Design
International Journal of Human-Computer Studies
TOWARDS OPTIMIZING ENTERTAINMENT IN COMPUTER GAMES
Applied Artificial Intelligence
Entertainment modeling through physiology in physical play
International Journal of Human-Computer Studies
Preference learning for cognitive modeling: a case study on entertainment preferences
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Power system database feature selection using a relaxed perceptron paradigm
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
Towards tailoring player experience in physical Wii games: a case study on relaxation
Proceedings of the International Conference on Advances in Computer Enterntainment Technology
Towards multiobjective procedural map generation
Proceedings of the 2010 Workshop on Procedural Content Generation in Games
Polymorph: dynamic difficulty adjustment through level generation
Proceedings of the 2010 Workshop on Procedural Content Generation in Games
Tanagra: a mixed-initiative level design tool
Proceedings of the Fifth International Conference on the Foundations of Digital Games
Proceedings of the Fifth International Conference on the Foundations of Digital Games
Towards affective camera control in games
User Modeling and User-Adapted Interaction
Modeling player performance in rhythm games
ACM SIGGRAPH ASIA 2010 Sketches
Evolving patch-based terrains for use in video games
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A game-based corpus for analysing the interplay between game context and player experience
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part II
Automatic level generation for platform videogames using genetic algorithms
Proceedings of the 8th International Conference on Advances in Computer Entertainment Technology
Towards a generic framework for automated video game level creation
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Search-based procedural content generation
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Proceedings of the 9th conference on Computing Frontiers
Evolving third-person shooter enemies to optimize player satisfaction in real-time
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
Digging deeper into platform game level design: session size and sequential features
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
Enhancing level difficulty and additional content in platform videogames through graph analysis
ACE'12 Proceedings of the 9th international conference on Advances in Computer Entertainment
Controllable procedural map generation via multiobjective evolution
Genetic Programming and Evolvable Machines
Design metaphors for procedural content generation in games
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Using Graph-Based Analysis to Enhance Automatic Level Generation for Platform Videogames
International Journal of Creative Interfaces and Computer Graphics
Skill-based Mission Generation: A Data-driven Temporal Player Modeling Approach
Proceedings of the The third workshop on Procedural Content Generation in Games
Hi-index | 0.00 |
This paper investigates the relationship between level design parameters of platform games, individual playing characteristics and player experience. The investigated design parameters relate to the placement and sizes of gaps in the level and the existence of direction changes; components of player experience include fun, frustration and challenge. A neural network model that maps between level design parameters, playing behavior characteristics and player reported emotions is trained using evolutionary preference learning and data from 480 platform game sessions. Results show that challenge and frustration can be predicted with a high accuracy (77.77% and 88.66% respectively) via a simple single-neuron model whereas model accuracy for fun (69.18%) suggests the use of more complex non-linear approximators for this emotion. The paper concludes with a discussion on how the obtained models can be utilized to automatically generate game levels which will enhance player experience.