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5

Both algorithms should give the same answer. However, their main difference is that alpha-beta does not explore all paths, like minimax does, but prunes those that are guaranteed not to be an optimal state for the current player, that is max or min. So, alpha-beta is a better implementation of minimax. Here are the time complexities of both algorithms ...


3

Some basic advantages of MCTS over Minimax (and its many extensions, like Alpha-Beta pruning and all the other extensions over that) are: MCTS does not need a heuristic evaluation function for states. It can make meaningful evaluations just from random playouts that reach terminal game states where you can use the loss/draw/win outcome. So if you're faced ...


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I'm not familiar with your game so I can't tell you what a good heuristic woul be in your specific case, but I can give you some advice on how to look for a good heuristic function. As a rule of thumb, the heuristic function for a MiniMax algorithm is best kept simple and efficient, so you can get deeper into the tree. But it depends on how costly it is to ...


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When combatting the horizon affect, you want to consider any short term actions that will greatly affect your position evaluation. Thus, in addition to captures, you will also want to include: When the opponent can make a king next move When the current player can make a king next move When the only legal moves left will lead to capture the turn after for ...


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I will answer the first question question based on information I have gathered so far. The probability of each action for the $\textbf{two player zero sum game}$ need not be the same for both players. It turns out that in the game of Morra, the probability vectors just turn out to be the same value. In general to determine $\textbf{optimal mixed strategies}$ ...


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There are a few different ways to improve on your simple heuristic approach, but they mostly resolve to these three things: Find a better heuristic. This could be done by calculating probabilities of results, or running loads of training simulations and somehow tuning the heuristic function. Look-ahead search/planning. There are many possible search ...


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