Description: The ‘End State’ refers to the desired outcome or condition upon completing a task or project. In the context of reinforcement learning, this term is crucial as it represents the goal that an agent seeks to achieve through interaction with its environment. In this framework, the end state can be seen as the objective guiding the agent’s behavior, influencing the decisions it makes to maximize its reward. On the other hand, in the realm of Kanban, the ‘End State’ relates to the culmination of a process or the delivery of a finished product. This concept is fundamental to the visual management of work, as it allows teams to clearly identify when a task has been completed and is ready for delivery. Clarity about the ‘End State’ helps avoid misunderstandings and keeps the workflow efficient, ensuring that all team members are aligned regarding expectations and desired outcomes. In summary, the ‘End State’ is a concept that encompasses both the achievement of goals in reinforcement learning and the completion of tasks in agile methodologies like Kanban, being essential for effective project planning and execution.
