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This survey provides a comprehensive overview of recent works that leverage sequence models such as the Transformer to solve sequential decision-making tasks. It discusses the connection between sequential decision-making and sequence modeling, and categorizes them based on the way they utilize the Transformer. The authors also summarize recent works that convert the reinforcement learning problem into sequential form to leverage sequence models for specific reinforcement learning settings.