Tic-Tac-Toe-AI | Invincible AI written in Go for Tic Tac Toe game | Artificial Intelligence library
kandi X-RAY | Tic-Tac-Toe-AI Summary
kandi X-RAY | Tic-Tac-Toe-AI Summary
Invincible AI written in Go for Tic Tac Toe game.
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Top functions reviewed by kandi - BETA
- Minimax returns the Minimax Packet for the given player
- NewGame creates a new game .
- NewMatrix returns a new matrix .
- Write a line
- NewController returns a Controller object .
- NewVector2 creates a new vector2 from x and y .
- NewBoardWriter returns a BoardWriter .
- NewSetup returns a new setup
- Check axis range
- Main entry point
Tic-Tac-Toe-AI Key Features
Tic-Tac-Toe-AI Examples and Code Snippets
Community Discussions
Trending Discussions on Tic-Tac-Toe-AI
QUESTION
const grabEmptySquares = (array) => {
var emptyGameSquares = [];
for (i = 0; i < 9; i++) {
if (!array[i]) emptyGameSquares.push(i);
}
return emptyGameSquares;
};
function findBestMove(board) {
var bestMove = {
index: null,
evaluation: null,
};
var availableMoves = grabEmptySquares(board);
availableMoves.forEach((move) => {
const simulGameboard = JSON.parse(JSON.stringify(board));
simulGameboard[move] = "o";
const evaluation = minimax(simulGameboard, 1, false);
const moveDetails = {
index: move,
evaluation: evaluation,
};
console.log(moveDetails)
if (evaluation > bestMove.evaluation || bestMove.evaluation === null) {
bestMove.index = move;
bestMove.evaluation = evaluation;
}
});
return bestMove.index;
}
function evaluate(board, isMaximizingPlayer, depth) {
var gameStatus = isGameOver(board);
if (gameStatus[0] != true) return;
if (gameStatus[1] === "win")
return isMaximizingPlayer ? +10 - depth : -10 + depth;
if (gameStatus[1] === "tie") return 0;
}
function minimax(board, depth, isMaximizingPlayer) {
var gameStatus = isGameOver(board);
if (gameStatus[0] == true) {
const evaluation = evaluate(board, !isMaximizingPlayer, depth);
return evaluation;
}
var simulGameboard = JSON.parse(JSON.stringify(board));
var availableMoves = grabEmptySquares(simulGameboard);
if (isMaximizingPlayer) {
bestVal = -Infinity;
availableMoves.forEach((move) => {
depth % 2 === 0
? (simulGameboard[move] = "o")
: (simulGameboard[move] = "x");
value = minimax(simulGameboard, depth + 1, false);
bestVal = Math.max(bestVal, value);
const moveDetails = {
index: move,
evaluation: bestVal,
depth: depth,
};
console.log(moveDetails);
});
return bestVal;
} else {
bestVal = Infinity;
availableMoves.forEach((move) => {
depth % 2 === 0
? (simulGameboard[move] = "o")
: (simulGameboard[move] = "x");
value = minimax(simulGameboard, depth + 1, true);
bestVal = Math.min(bestVal, value);
const moveDetails = {
index: move,
evaluation: bestVal,
depth: depth,
};
console.log(moveDetails);
});
return bestVal;
}
}
function isGameOver(array) {
var gameOver = false;
if (
(array[0] && array[0] === array[1] && array[0] === array[2]) ||
(array[3] && array[3] === array[4] && array[3] === array[5]) ||
(array[6] && array[6] === array[7] && array[6] === array[8])
) {
return (gameOver = [true, "win"]);
}
if (
(array[0] && array[0] === array[4] && array[0] === array[8]) ||
(array[2] && array[2] === array[4] && array[2] === array[6])
) {
return (gameOver = [true, "win"]);
}
if (
(array[1] && array[1] === array[4] && array[4] === array[7]) ||
(array[0] && array[0] === array[3] && array[3] === array[6]) ||
(array[2] && array[2] === array[5] && array[5] === array[8])
) {
return (gameOver = [true, "win"]);
}
if ([...array].every((index) => index)) {
return (gameOver = [true, "tie"]);
}
return (gameOver = [false, null]);
}
...ANSWER
Answered 2021-Apr-08 at 01:07This isn't the easist code to read, but AFAICT the minimax
function copies the game board state once and then loops through possible moves with availableMoves.forEach
. This means that when evaluating each possible move, it acts as if each previously considered move had been made. Move the copy inside the forEach and things should make somewhat more sense.
You already have this in the findBestMove
function. I'd strongly suggest unifying findBestMove
and minimax
(and the sides of the isMaximizingPlayer
branch inside minimax
). Having very similar code in multiple places makes it hard to remember where you have and haven't fixed things.
I'd also suggest replacing the isMaximizingPlayer
and depth%2
logic with a player
variable that can be either "x" or "o", and multiplying goodness scores by -1 as needed. It'll be easier to keep track of.
QUESTION
I have implemented Minimax Algorithm for Tic Tac Toe Game from GeeksForGeeks. I know how the Minimax Algorithm works but my code here doesn't work according to it. I have checked and checked for the things I might be doing wrong and also have debugged it. But it seems, I am not able to find it.
Please look into the algorithm, it would be much thankful for extra set of eyes and to find the incorrect part which I can't seem to find.
I have commented every part of the code that is helpful with Minimax Algorithm. I think it would be easy to catch up.
Please help me out here.
Thank you.
...ANSWER
Answered 2020-Sep-15 at 13:23There a mismatch between your function checkForSpace()
and its use in minimax()
. If there is space left you return false
and if you get a false
in minimax()
you stop the search as if there is a tie. You need to invert the boolean in checkForSpace()
or remove the logical not in minimax()
.
You should propably rename checkForSpace()
and other function that return a boolean. From The Art of Readable Code (Dustin Boswell and Trevor Foucher):
When picking a name for a boolean variable or a function that returns a boolean, be sure it’s clear what
true
andfalse
really mean.Here’s a dangerous example:
QUESTION
i'm trying to make a unbeatable tic tac toe for a side project and i can't make it right (i can actually beat it ironically). It's actually a implementation of the MiniMax algorithm; i came with this code
...ANSWER
Answered 2020-Aug-24 at 13:11There are multiple bugs in your code:
- You are checking the value of
grid[0][0]
ingrid[0][2] == grid[1][1] && grid[0][2] == grid[2][0]
case of the functionevaluateBoard
. It should begrid[0][2]
. playerMov(grid);
in the functionplayerMov
should bereturn playerMov(grid);
. Otherwise, the re-entered "correct" values will be dropped and (partly) uninitalizedplayerMov
will be returned.- You should update
best
tomoveValue
whenmoveValue > best
in the functionfindMove
. (this should be the cause of the issue on your question)
QUESTION
I have a game of Tic Tac Toe that uses the Minimax Algorithm. I want to improve that by adding alpha-beta pruning. However the alpha-beta method does not seem to be able to calculate moves effectively. It just puts its piece in the next available space whether it is the optimal move or not. I do not have this issue with the minimax method. I sure it’s something simple that I keep overlooking, so forgive me. I used this tutorial for minimax and this tutorial for alpha-beta pruning.
This is the Minimax class. It includes the alpha-beta method:
...ANSWER
Answered 2018-Feb-02 at 19:41Alpha-Beta Pruning requires a good evaluation function for unfinished game states to be effective. It should be able to evaluate when one player is "more likely" to win accurately. It will use the evaluation to prune variations that do not look promising.
Right now your evaluation function only differentiates between game over and game in progress, so you will not be able to do better than min-max.
However, if you are doing worse than min-max, you must also have a bug somewhere else. I recommend stepping through the code and trying to see where it goes wrong.
QUESTION
I am trying to make a tic tac toe game with the minimax algorithm. I am using this tutorial. While I understand how this algorithm works I am having trouble implementing it. I cannot get this algorithm to pass a unit test. It gives me an exception for cells that are occupied in the board and I cannot find a solution by myself. It should return the winning index in the board. Thanks for your help.
Here is the failed test response:
...ANSWER
Answered 2017-Oct-27 at 19:20When your recursion finishes a branch, you are setting a move already evaluated back to Token.EMPTY
so you can perform a branch on another move. I don't think it's a logic bug.
QUESTION
I am trying to build tic-tac-toe AI using min max algorithm. I was referring to this post from geekforgeeks for writing my code. But strangely when I'm using 1D array instead of 2D array by modifying the code as given below, I'm not getting the right output from findBestMove function. It is supposed to return index as 4, but it always returns 2. what am I doing wrong?
...ANSWER
Answered 2017-Jun-11 at 07:56In function evaluate2
, you loop like this:
QUESTION
I have been trying to use minimax algorithm for my tic tac toe game to make my AI unbeatable. However it doesn't always return the optimal move.
...ANSWER
Answered 2017-Jun-03 at 18:58If you see the moveVal
for each i
you'll see that it's zero.
That's because in the minimax function you call isMovesLeft
which when false returns 0.
The problem with your program is that isMovesLeft
always returns false
.
You should change it to :
QUESTION
I am new to web development and am referring following link-
Please find below js, css and html file respectively.
We are not having any element with class="selected" but still project is running perfectly
...ANSWER
Answered 2017-Apr-27 at 12:26Toggle behavior - if the element has a class, the class will be removed. If the element hasn't got the class, the class will be added. In this case there are no elements with .select class, but it will be added after toggleClass('selected') executes. I commented every js line for you.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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