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Found 11 papers, 0 papers with code
Playing With Neuroscience: Past, Present and Future of Neuroimaging and Games
what can we expect from the future?
Difficulty Modelling in Mobile Puzzle Games: An Empirical Study on Different Methods to Combine Player Analytics and Simulated Data
Difficulty is one of the key drivers of player engagement and it is often one of the aspects that designers tweak most to optimise the player experience; operationalising it is, therefore, a crucial task for game development studios.
Procedurally generating rules to adapt difficulty for narrative puzzle games
This paper focuses on procedurally generating rules and communicating them to players to adjust the difficulty.
Estimating player completion rate in mobile puzzle games using reinforcement learning
In this work we investigate whether it is plausible to use the performance of a reinforcement learning (RL) agent to estimate the difficulty measured as the player completion rate of different levels in the mobile puzzle game Lily's Garden. For this purpose we train an RL agent and measure the number of moves required to complete a level.
Creating user stereotypes for persona development from qualitative data through semi-automatic subspace clustering
Designing with personas involves the production of descriptions of fictitious users, which are often based on data from real users.
Procedural content generation of puzzle games using conditional generative adversarial networks
In this article, we present an experimental approach to using parameterized Generative Adversarial Networks (GANs) to produce levels for the puzzle game Lily's Garden.
Combining Sequential and Aggregated Data for Churn Prediction in Casual Freemium Games
In freemium games, the revenue from a player comes from the in-app purchases made and the advertisement to which that player is exposed.
Predicting Customer Lifetime Value in Free-to-Play Games
As game companies increasingly embrace a service-oriented business model, the need for predictive models of players becomes more pressing.
Personalized Game Difficulty Prediction Using Factorization Machines
The accurate and personalized estimation of task difficulty provides many opportunities for optimizing user experience.
Statistical Modelling of Level Difficulty in Puzzle Games
The model is fitted and evaluated on a dataset collected from the game Lily's Garden by Tactile Games, and the results of the evaluation show that the it is able to describe and explain difficulty in a vast majority of the levels.
Strategies for Using Proximal Policy Optimization in Mobile Puzzle Games
While traditionally a labour intensive task, the testing of game content is progressively becoming more automated.
