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In order to identify computer network attacks, this paper introduces a hybrid model for creating an intrusion detection system. The proposed model uses in\u2010depth reinforcement learning to create an intelligent agent with a high understanding of the data being transmitted over the network to be able to detect network attacks well. The proposed model also uses PCA to represent new data because agent training is highly dependent on input data. The NSL\u2010KDD dataset, besides the CTU\u201013 dataset, has been used as a standard dataset to train and test the proposed model, and in the training phase, an attempt has been made to overcome its challenges. 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