Improving Human Players’ T-Spin Skills in Tetris with Procedural Problem Generation
| Autor: | Chu-Hsuan Hsueh, Kokolo Ikeda, Taishi Oikawa |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
050101 languages & linguistics
Computer science 05 social sciences Training system ComputingMilieux_PERSONALCOMPUTING 02 engineering and technology Field (computer science) Entertainment Human–computer interaction Content generation 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 0501 psychology and cognitive sciences Spin (aerodynamics) |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783030658823 ACG |
| DOI: | 10.1007/978-3-030-65883-0_4 |
| Popis: | Researchers in the field of computer games interest in creating not only strong game-playing programs, but also programs that can entertain or teach human players. One of the branches is procedural content generation, aiming to generate game contents such as maps, stories, and puzzles automatically. In this paper, automatically generated puzzles are used to assist human players in improving the playing skills for the game of Tetris, a famous and popular tile-matching game. More specifically, a powerful technique called T-spin is hard for beginners to learn. To assist beginners in mastering the technique, automatically generated two-step to T-spin problems are given for them to solve. Experiments show that the overall ability for beginners to complete T-spin during play is improved after trained by the given problems. The result demonstrates the possibility of using automatically generated problems to assist human players in improving their playing skills. |
| Databáze: | OpenAIRE |
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