Monte Carlo Tree Search in 60 Seconds | Machine Learning Algorithms

? Monte Carlo Tree Search in 60 Seconds | Machine Learning Algorithms ? The Hitchhiker&Guide to Machine Learning Algorithms | by @serpdotai --- -- Monte Carlo Tree Search (MCTS) is like a treasure hunter exploring a vast uncharted island to find the most valuable treasure hidden in it. Initially, the treasure hunter explores a path on the island which leads him to a final point, where he gets the value of the treasure in that path. By following this process multiple times, he constructs a tree of paths with their corresponding values of treasure. Finally, he chooses the most promising path with the highest average value of treasure that leads him to the most valuable treasure on the island. Similarly, MCTS, in a given state of the game, simulates a random game to the end and updates the value of the played moves based on the game&result. It repeats this process many times to build a tree of explored game states. When deciding on the actual move to play, MCTS chooses the move that leads to the most promising state, i.e., the state with the highest average result obtained from simulations. Monte Carlo Tree Search, often abbreviated as MCTS, is a best-first, rollout- based tree search algorithm that has gained popularity in the field of artificial intelligence. This heuristic search algorithm starts by simulating a random game to the very end, and then updates the value of the played moves based on the game&result. This process is repeated many times, each time building...