Continuous Reinforcement Learning-based Dynamic Difficulty Adjustment in a Visual Working Memory Game

• URL: http://arxiv.org/abs/2308.12726v1
• Date: Thu, 24 Aug 2023 12:05:46 GMT
• Title: Continuous Reinforcement Learning-based Dynamic Difficulty Adjustment in a Visual Working Memory Game
• Authors: Masoud Rahimi, Hadi Moradi, Abdol-hossein Vahabie, Hamed Kebriaei
• Abstract summary: Reinforcement Learning (RL) methods have been employed for Dynamic Difficulty Adjustment (DDA) in non-competitive games. We propose a continuous RL-based DDA methodology for a visual working memory (VWM) game to handle the complex search space for the difficulty of memorization.
• Score: 5.857929080874288
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Dynamic Difficulty Adjustment (DDA) is a viable approach to enhance a player's experience in video games. Recently, Reinforcement Learning (RL) methods have been employed for DDA in non-competitive games; nevertheless, they rely solely on discrete state-action space with a small search space. In this paper, we propose a continuous RL-based DDA methodology for a visual working memory (VWM) game to handle the complex search space for the difficulty of memorization. The proposed RL-based DDA tailors game difficulty based on the player's score and game difficulty in the last trial. We defined a continuous metric for the difficulty of memorization. Then, we consider the task difficulty and the vector of difficulty-score as the RL's action and state, respectively. We evaluated the proposed method through a within-subject experiment involving 52 subjects. The proposed approach was compared with two rule-based difficulty adjustment methods in terms of player's score and game experience measured by a questionnaire. The proposed RL-based approach resulted in a significantly better game experience in terms of competence, tension, and negative and positive affect. Players also achieved higher scores and win rates. Furthermore, the proposed RL-based DDA led to a significantly less decline in the score in a 20-trial session.

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