minimax

问题 I'm making a Tic-Tac-Toe program. I plan to use minimax with it. I made a tree with space for all possible game sequences and I'm looking for a way to populate it. I currently have this type: typedef struct name { char grid [3] [3]; struct name * child [9]; } node; and I'm looking for a way to fill grid just like it's shown here. How would I go filling the grid to make sure that all possible combinations are there? My plan is to have the game recognize every move player can take and then

问题 Summary of my objective: Figure out how to use continuation-passing style to avoid a stack overflow when using an algorithm I believe cannot be made tail-recursive. Alternatively, find a way to make the function tail-recursive. Details: I am new to F# (and functional programming in general) and I am attempting to implement the minimax algorithm with alpha-beta pruning. This is an algorithm used to determine the best possible move for a two-player game. The pseudocode for the algorithm can be

问题 I'm here to ask a specific topic - I really found few info about this on the web. I'm implementing a F# version of Minimax algorithm. The problem I'm having now is that I want to compare Leaf of my tree (data structure below). Searching the erros the VS gave to me I arrived to something like this: The tree type I used to have: type TreeOfPosition = | LeafP of Position | BranchP of Position * TreeOfPosition list and the temptative for implementing the IComparable type staticValue = int [

问题 I am new to game tree algorithms, and i've tried to implement a simple tictactoe game which utilizes the NegaMax algorithm to evaluate tile scores for the computer AI player. However, the AI behaves not in a smart way (i can win all the time, because the AI does not block my moves), and i think i implemented the NegaMax algorithm wrongly. If anyone could help me with the following code, it would be great. I spent such a long time trying different things out, but i never got it to work.

问题 I am working on a Minimax algorithm for unbeatable Tic Tac Toe. I need it to work both for when the Computer goes first as well as when the Player goes first. With the current version, the Computer will never lose when going first. However, it seems that Minimax never finds a best move (always returns -1 as the score) if the Player goes first. What is causing the Minimax score returned to be -1 for the Computer if the Player makes the first move? Example: board.addMark( 1, Mark2.PLAYER ); //

问题 I have created a Tic-Tac-Toe game on a microcontroller, including a perfect AI (perfect meaning that it doesn't lose). I did not use a minimax algorithm for that, just a little state machine with all possible and optimal moves. My problem now is that I wanted to implement different difficulties (Easy, Medium and Hard). The AI so far would be the hard one. So I've thought about how to do this the best way and ended up wanting to use the minimax algorithm but in a way that it calculates all the

问题 I am trying to implement in python Donald Knuth's algorithm for codebreaking mastermind in not more than 5 moves. I have checked my code several times, and it seems to follow the algorithm, as its stated here: http://en.wikipedia.org/wiki/Mastermind_(board_game)#Five-guess_algorithm However, I get that some of the secrets take 7 or even 8 moves to accomplish. Here is the code: #returns how many bulls and cows there are def HowManyBc(guess,secret): invalid=max(guess)+1 bulls=0 cows=0 r=0 while

问题 I am trying to implement in python Donald Knuth's algorithm for codebreaking mastermind in not more than 5 moves. I have checked my code several times, and it seems to follow the algorithm, as its stated here: http://en.wikipedia.org/wiki/Mastermind_(board_game)#Five-guess_algorithm However, I get that some of the secrets take 7 or even 8 moves to accomplish. Here is the code: #returns how many bulls and cows there are def HowManyBc(guess,secret): invalid=max(guess)+1 bulls=0 cows=0 r=0 while

问题 I've written a minimax algorithm with alpha beta pruning for the game Checkers, and now I'm trying to rewrite it using the negamax approach. I'm expecting the two to be equivalent, since negamax is just a technique to write the minimax. But for some reason my two algorithms behave differently. When I run them both on the same input, the negamax version seems to evaluate more states, so I think something must be wrong with the alpha beta pruning. The code below shows both algorithms ( minimax

问题 I want to implement the Minimax algorithm in java. I couldnt find a good tree representation. Is there an existing one or should I make my own? by the way this is for the pacman game Thanks 回答1: You don't need one. The minimax algorithm is frequently illustrated with a tree. However, that tree represents the steps taken by the algorithm to choose the best move. It is not a data structure held by the algorithm. Instead, you'll use iteration and recursion . At each interior node of the tree,