Improved Feature Learning: A Maximum-Average-Out Deep Neural Network for the Game Go
المؤلفون المشاركون
Liu, Bo
Li, Xiali
Lv, Zhengyu
Wu, Licheng
Wang, Zheng
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-6، 6ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-04-09
دولة النشر
مصر
عدد الصفحات
6
التخصصات الرئيسية
الملخص EN
Computer game-playing programs based on deep reinforcement learning have surpassed the performance of even the best human players.
However, the huge analysis space of such neural networks and their numerous parameters require extensive computing power.
Hence, in this study, we aimed to increase the network learning efficiency by modifying the neural network structure, which should reduce the number of learning iterations and the required computing power.
A convolutional neural network with a maximum-average-out (MAO) unit structure based on piecewise function thinking is proposed, through which features can be effectively learned and the expression ability of hidden layer features can be enhanced.
To verify the performance of the MAO structure, we compared it with the ResNet18 network by applying them both to the framework of AlphaGo Zero, which was developed for playing the game Go.
The two network structures were trained from scratch using a low-cost server environment.
MAO unit won eight out of ten games against the ResNet18 network.
The superior performance of the MAO unit compared with the ResNet18 network is significant for the further development of game algorithms that require less computing power than those currently in use.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Li, Xiali& Lv, Zhengyu& Liu, Bo& Wu, Licheng& Wang, Zheng. 2020. Improved Feature Learning: A Maximum-Average-Out Deep Neural Network for the Game Go. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-6.
https://search.emarefa.net/detail/BIM-1193196
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Li, Xiali…[et al.]. Improved Feature Learning: A Maximum-Average-Out Deep Neural Network for the Game Go. Mathematical Problems in Engineering No. 2020 (2020), pp.1-6.
https://search.emarefa.net/detail/BIM-1193196
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Li, Xiali& Lv, Zhengyu& Liu, Bo& Wu, Licheng& Wang, Zheng. Improved Feature Learning: A Maximum-Average-Out Deep Neural Network for the Game Go. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-6.
https://search.emarefa.net/detail/BIM-1193196
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1193196
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر