Credit assignment is the process of determining which actions or decisions are responsible for achieving a particular outcome in learning systems, particularly in reinforcement learning. This concept is vital because it affects how agents learn from their environment and adjust their behavior based on rewards or punishments received after taking specific actions. Understanding credit assignment helps in creating models that can efficiently learn and adapt over time by accurately associating rewards with the appropriate actions that led to them.
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