Using edges in Monte Carlo Tree Search

#ArtificialIntelligence: Using edges in Monte Carlo Tree Search

All the articles I’ve read on Monte Carlo Tree Search implementation seem only concerned with storing states and children in tree nodes. I haven’t seen a single implementation that uses edges to store moves and connect nodes. Why is that? Wouldn’t it make sense to have a way to see which move leads to which state?

When updating the root node to match the current board state, I’m thinking that it would be easier to compare the opponents move to all possible moves and find the one that matches than it would be to compare the new board state to all possible board states to find the one that matches. Am I wrong?

submitted by /u/Neoflash_1979 to r/artificial
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