Eligibility Traces

This lecture introduces eligibility traces, a concept of enormous practical importance in reinforcement learning. The instructor explains how eligibility traces enable reward information to travel more rapidly, addressing the problem of slow information flow in online TD algorithms. The solution presented is the use of eligibility traces in SARSA(2), where memory of previous state-action pairs is kept and updated over time. The lecture covers the implementation of eligibility traces in SARSA(2) and provides a detailed explanation of the algorithm. A quiz at the end tests the understanding of eligibility traces and their role in reinforcement learning.