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Automated planning and scheduling are critical components of artificial intelligence systems, enabling efficient decision-making in complex and dynamic environments. This paper provides a comprehensive review of automated planning and scheduling techniques, highlighting their importance in AI applications. We discuss key concepts, algorithms, and methodologies used in automated planning and scheduling, focusing on their strengths, limitations, and recent advancements. Additionally, we explore the integration of planning and scheduling with other AI techniques, such as machine learning and constraint satisfaction, to enhance decision-making capabilities. Through this analysis, we aim to provide insights into the current state of automated planning and scheduling in AI and identify future research directions.