Abstract
Player-centered approaches that aim to maximize player enjoyment have been steady, but with poor heuristics that do not rely on any particular theory of entertainment. Certainly, the Theory of Flow is the most referred in the game AI area and, still, it is unclear how to effectively design and implement adaptive game modules or understanding which game features drive players to a flow state. Therefore, in this document we perform a systematic analysis of literature aimed to enhance our knowledge about how to adapt flow heuristics to a video game context. This analysis endows us with the knowledge needed to define a flow framework for game AI. Our framework, FlowAI, describes which modules and what gameplay features can be adapted to design an effective video game intended to facilitate the achievement of flow in players. Furthermore, from our framework standpoint, we identify and review existing work that could be adjusted to foster flow. Our aim with this analysis is to identify current challenges, and motivate new directions in the player-centered research area.
Highlights
Author keywords DDS; Dynamic difficulty scaling; Game AI; Immersion; Personalized; Player modeling; Playercentered; Theory of flow
Furthermore, from our framework standpoint, we identify and review existing work that could be adjusted to foster flow
Engineering uncontrolled terms Game AI; Immersion; Personalized; Player modeling; Playercentered; Theory of flow
Summary
Author keywords DDS; Dynamic difficulty scaling; Game AI; Immersion; Personalized; Player modeling; Playercentered; Theory of flow.
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