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pro vyhledávání: '"Roohi, Shaghayegh"'
Autor:
Roohi, Shaghayegh, Guckelsberger, Christian, Relas, Asko, Heiskanen, Henri, Takatalo, Jari, Hämäläinen, Perttu
This paper presents a novel approach to automated playtesting for the prediction of human player behavior and experience. It has previously been demonstrated that Deep Reinforcement Learning (DRL) game-playing agents can predict both game difficulty
Externí odkaz:
http://arxiv.org/abs/2107.12061
We propose a novel simulation model that is able to predict the per-level churn and pass rates of Angry Birds Dream Blast, a popular mobile free-to-play game. Our primary contribution is to combine AI gameplay using Deep Reinforcement Learning (DRL)
Externí odkaz:
http://arxiv.org/abs/2008.12937