This lecture focuses on minimizing the total cost incurred by an algorithm by selecting the best sequence of actions. The instructor explains how to increase the probability of good actions and decrease the probability of bad actions through a loss vector. The performance theorem is presented, showing that the algorithm reaches optimal performance. The lecture also covers the initialization process, proof of concept, and the infeasibility of certain systems.
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