Hi please help with this and each part. I Have no idea what's going on.

The partial game tree below was discussed in class on the topic of Monte Carlo tree search. Each node shows the win rate Nw : number of playout wins / total number of playouts from that node's parent. The leaf node labeled 0/0 was just expanded in the middle of a MCTS iteration. 1. Suppose that a rollout is performed and the player corresponding to the orange nodes (second and fourth layers) wins. Give the new win rates of all nodes that are updated in order from leaf to root (either the w or N values or both). 2. Using the new win rates and the exploration parameter =1, compute the UCT values of each of the nodes in the second layer of the tree (immediate children of the root node). Which of these three nodes is traversed by the selection policy in the next MCTS iteration? 3. Solve for the minimum value of for which a different child node of the root would be selected. Explain why we need a higher, not lower, value than that in part 2 in order to select one of the other two nodes. 4. Briefly explain why the UCT selection policy never completely eliminates the possibility of selecting any tree node, even if it has a very low (or even zero) win rate. Assume >0