Eligibility Traces

Eligibility traces are a concept in reinforcement learning that help algorithms learn from experience more efficiently. Think of them as a temporary memory that keeps track of recent actions and states, giving credit or blame to those earlier steps when new feedback is received. This way, the system can assign appropriate importance to actions that led to a certain outcome, even if some time has passed. It’s like a short-term “record” that helps the learning process connect causes and effects more effectively, improving decision-making over time.