Conference proceeding
Dynamically Extracting Play Style in Educational Games
19TH INTERNATIONAL CONFERENCE ON INTELLIGENT GAMES AND SIMULATION (GAME-ON(R) 2018), pp.37-46
01 Jan 2018
Abstract
Player modeling is a key aspect for game personalization. However, most existing works consider play style as a static characteristic of the player. This is far from true, since players often change their play style especially in long gameplay sessions. To overcome this limitation, we aim at dynaimically extracting the play style and use it in customizing the game on-the-fly to each individual player during the game. To this end, we have designed a framework that automatically recognizes players' play styles that can equip the system with the ability to adapt the game session by session. Hereby we evaluate our proposed framework in the context of an educational game called Solving the Incognitum.
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Details
- Title
- Dynamically Extracting Play Style in Educational Games
- Creators
- Reza Khoshkangini - Fdn Bruno Kessler FBK, Trento, ItalyAnnapaola Marconi - Fdn Bruno Kessler FBK, Trento, ItalySantiago Ontanon - Drexel UniversityJichen Zhu - Drexel University
- Contributors
- D King (Editor)
- Publication Details
- 19TH INTERNATIONAL CONFERENCE ON INTELLIGENT GAMES AND SIMULATION (GAME-ON(R) 2018), pp.37-46
- Conference
- 19TH INTERNATIONAL CONFERENCE ON INTELLIGENT GAMES AND SIMULATION (GAME-ON(R) 2018), 19th
- Publisher
- Eurosis
- Number of pages
- 10
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science (Computing); Digital Media
- Identifiers
- 991019170551604721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Software Engineering
- Computer Science, Theory & Methods