团队配对MOBA游戏的反向传播神经网络实验

E. Tanuar, B. S. Abbas, A. Trisetyarso, C. Kang, F. Gaol, W. Suparta
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引用次数: 4

摘要

反向传播是一种著名的学习方法,在游戏中实现反向传播技术是游戏人工智能的一部分。本文旨在利用神经网络分析Moba类游戏在学习中的最佳团队组成。手机传奇:Bang Bang是一款MOBA手机游戏。本实验采用2隐层反向传播神经网络算法对手机传奇游戏进行分析。为了达到稳定性,进行了5000步的训练。这也是一种学习在团队比赛中找到最佳构图的方法。人工智能和游戏领域的研究是非常广泛和开放的,未来有很大的机会可以探索。本研究的目的是产生良好的团队组合,这可以导致更大的获胜机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Back propagation neural network experiment on team matchmaking MOBA game
Backpropagation is one of the famous method for learning, Implementing Backpropagation techniques in games is part of AI in game. This paper aim to analyzed the best team composition in a Moba Game type in learning using neural network. Mobile Legend: Bang Bang is one of MOBA game for mobile phone. In this experiment, the 2 hidden layers back-propagation neural network algorithm is used to analyze the Mobile Legend game. 5000 training steps was done to reach the stability. This also a way of learning to find the best composition in a team played. Research in area AI and game is very wide and open, a huge opportunity to be explore in future. The objective of this research is to produce the good combination of team which can be resulted in a greater winning chance.
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