2026-06-29T02:33:44Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/1310302026-01-27T01:15:40Zcom_20.500.14352_14col_20.500.14352_15

Measuring Control to Dynamically Induce Flow in Tetris Lora Ariza Diana Sánchez Ruiz-Granados, Antonio Alejandro González Calero, Pedro Antonio Camps Ortueta Irene Dynamic difficulty adjustment (DDA) is a set of techniques that aim to automatically adapt the difficulty of a video game based on the player’s performance. This article presents a methodology for DDA using ideas from the theory of flow and case-based reasoning (CBR). In essence, we are looking to generate game sessions with a similar difficulty evolution to previous game sessions that have produced flow in players with a similar skill level. We propose a CBR approach to dynamically assess the player’s skill level and adapt the difficulty of the game based on the relative complexity of the last game states. We develop a DDA system for Tetris using this methodology and show, in an experiment with 40 participants, that the DDA version has a measurable impact on the perceived flow using validated questionnaires. 2026-01-26T15:33:37Z 2026-01-26T15:33:37Z 2026-01-26T15:33:37Z 2022-12-01 journal article https://hdl.handle.net/20.500.14352/131030 XXXX-XXXX 10.1109/TG.2022.3182901 eng Diana Sofía Lora Ariza, Antonio A. Sánchez-Ruiz, Pedro Antonio González-Calero, Irene Camps-Ortueta: Measuring Control to Dynamically Induce Flow in Tetris. IEEE Trans. Games 14(4): 579-588 (2022) open access IEEE