This article focuses on the application of deep learning techniques in sequential games. The main hypothesis is that sequence to sequence learning approach is applicable and demonstrate better performance than classic reinforcement learning. So autonomous agents trough sequence to sequence approach are capable of discovering good solutions to the problem at hand by learning in dynamic environment.