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- W2893337095 abstract "In this paper, Profit Sharing using convolutional neural network is realized. In the proposed method, action value in Profit Sharing is learned by convolutional neural network. This is a method that learns the value function of Profit Sharing instead of the value function of Q Learning used in the Deep Q-Network. By changing to an error function based on the value function of Profit Sharing which can acquire probabilistic policy in a shorter time, the proposed method is able to learn in a shorter time than the conventional Deep Q-Network. Computer experiments were carried out on Asterix of Atari 2600, and the proposed method was compared with the conventional Deep Q-Network. As a result, we confirmed that the proposed method can learn from the earlier stage than Deep Q-Network and can obtain higher score finally." @default.
- W2893337095 created "2018-10-05" @default.
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- W2893337095 date "2018-01-01" @default.
- W2893337095 modified "2023-09-27" @default.
- W2893337095 title "Learning Game by Profit Sharing Using Convolutional Neural Network" @default.
- W2893337095 cites W2112796928 @default.
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- W2893337095 doi "https://doi.org/10.1007/978-3-030-01418-6_5" @default.
- W2893337095 hasPublicationYear "2018" @default.
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