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2022 AAAI AAAI 2022

UCSM-DNN: User and Card Style Modeling with Deep Neural Networks for Personalized Game AI

Abstract

Abstract This paper tries to resolve long waiting time to find a matching person in player versus player mode of online sports games, such as baseball, soccer and basketball. In player versus player mode, game playing AI which is instead of player needs to be not just smart as human but also show variety to improve user experience against AI. Therefore a need to design game playing AI agents with diverse personalized styles rises. To this end, we propose a personalized game AI which encodes user style vectors and card style vectors with a general DNN, named UCSM-DNN. Extensive experiments show that UCSM-DNN shows improved performance in terms of personalized styles, which enrich user experiences. UCSM-DNN has already been integrated into popular mobile baseball game: MaguMagu 2021 as personalized game AI.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Deep Learning and Machine Learning and Reinforcement Learning
🧭 Keyword Pioneer — personalized ai
🐣 Hot Topic Early Bird — game ai
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Daegeun Choe , Youngbak Jo , Shindong Kang , Shounan An , Insoo Oh

Topics

Artificial Intelligence > Core AI > Game AI Machine Learning > Application Areas > Domain Adaptation Deep Learning > Architectures > Neural Networks Reinforcement Learning > Applications > Game AI Deep Learning > Learning Types > Deep Learning

Keywords

user modeling deep neural network game ai style vector style modeling personalized ai personalized game ai
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