Explore a groundbreaking approach to AI planning in this 26-minute video explanation of the paper "Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning." Delve into a novel generalization of Monte Carlo Tree Search (MCTS) that revolutionizes problem-solving by recursively dividing complex tasks into manageable sub-problems. Learn how this method deviates from traditional step-by-step planning, instead focusing on identifying optimal intermediate goals. Discover the algorithm's unique ability to improve imperfect goal-directed policies through strategic sub-goal sequencing. Examine the concept of Divide-and-Conquer MCTS (DC-MCTS) and its application in both grid-world navigation and challenging continuous control environments. Gain insights into the flexibility of planning strategies and their potential to outperform sequential planning approaches.