针对2048游戏，有人实现了一个AI程序，可以以较大概率（高于90%）赢得游戏，并且作者在
stackoverflow上简要介绍了AI的算法框架和实现思路。

有博客介绍了其中涉及的算法，讲的很好

其中算法的主要是在ai.js文件中。我加了很多的注释在其中，方便大家理解。

function AI(grid) {this.grid = grid;
}// static evaluation function
AI.prototype.eval = function() {var emptyCells = this.grid.availableCells().length;//各种计算的权重，可以自己手动的调试var smoothWeight = 0.1,//monoWeight   = 0.0,//islandWeight = 0.0,mono2Weight  = 1.0,emptyWeight  = 2.7,maxWeight    = 1.0;return this.grid.smoothness() * smoothWeight//+ this.grid.monotonicity() * monoWeight//- this.grid.islands() * islandWeight+ this.grid.monotonicity2() * mono2Weight+ Math.log(emptyCells) * emptyWeight+ this.grid.maxValue() * maxWeight;
};// alpha-beta depth first search
AI.prototype.search = function(depth, alpha, beta, positions, cutoffs) {var bestScore;var bestMove = -1;var result;// the maxing playerif (this.grid.playerTurn) {bestScore = alpha;//遍历四个方向for (var direction in [0, 1, 2, 3]) {var newGrid = this.grid.clone();//逐一搜寻方向if (newGrid.move(direction).moved) {positions++;//如果已经赢了直接返回if (newGrid.isWin()) {return { move: direction, score: 10000, positions: positions, cutoffs: cutoffs };}//如果还没有赢得话就继续想下走var newAI = new AI(newGrid);//当深度为0的时候停止if (depth == 0) {result = { move: direction, score: newAI.eval() };} else {//继承父节点的alpha//递归的搜寻  注意每移动一次轮次翻转 player->computer->player->computer->....result = newAI.search(depth-1, bestScore, beta, positions, cutoffs);if (result.score > 9900) { // winresult.score--; // to slightly penalize higher depth from win} positions = result.positions;cutoffs = result.cutoffs;}//如果返回的分数>当前最好分数则给bestScore和bestMove重新赋值if (result.score > bestScore) {bestScore = result.score;bestMove = direction;}//如果最好的分数大于beta也即意味着上一层节点不会继续向下走 切分if (bestScore > beta) {cutoffs++//既然不会往这儿走，那么分数还是你上层的betareturn { move: bestMove, score: beta, positions: positions, cutoffs: cutoffs };}}}}else { // computer's turn, we'll do heavy pruning to keep the branching factor lowbestScore = beta;// try a 2 and 4 in each cell and measure how annoying it is// with metrics from evalvar candidates = [];//得到可以填充块的坐标var cells = this.grid.availableCells();//分数为2 或者 4var scores = { 2: [], 4: [] };for (var value in scores) {for (var i in cells) {scores[value].push(null);var cell = cells[i];var tile = new Tile(cell, parseInt(value, 10));this.grid.insertTile(tile);//算出分数，下面的计算可以看出要算出分数最大的，我们知道min节点是使游戏变得更难//那么smoothness要越小越好，所以加上符号(越大越好) islands意味着有数字的格子，当然越多越好//通俗理解就是不能合并在一起的越多越好scores[value][i] = -this.grid.smoothness() + this.grid.islands();this.grid.removeTile(cell);}}// now just pick out the most annoying movesvar maxScore = Math.max(Math.max.apply(null, scores[2]), Math.max.apply(null, scores[4]));for (var value in scores) { // 2 and 4//将最大分数的候选者选出来（满足最大分数的可能不止一个）for (var i=0; i<scores[value].length; i++) {if (scores[value][i] == maxScore) {candidates.push( { position: cells[i], value: parseInt(value, 10) } );}}}// search on each candidatefor (var i=0; i<candidates.length; i++) {var position = candidates[i].position;var value = candidates[i].value;var newGrid = this.grid.clone();var tile = new Tile(position, value);newGrid.insertTile(tile);newGrid.playerTurn = true;positions++;newAI = new AI(newGrid);//min节点往下的alpha还是上层的，beta是最好的分数，也就是说下层节点如果你取得的最大值只能是beta，//如果大于beta我会把你pass掉result = newAI.search(depth, alpha, bestScore, positions, cutoffs);positions = result.positions;cutoffs = result.cutoffs;//竟然有比beta还小的分数，好，我选择你if (result.score < bestScore) {bestScore = result.score;}//如果最好的分数小于上层的下界 意味着上层节点肯定不会继续向下走if (bestScore < alpha) {cutoffs++;//返回的分数是还是上层的值也就是说你反正不会走我这条路，那你的分数还是你原来的分数//关于此处的move:null 注意上面的result的depth是继承父节点的，意味着depth>0//也就是说最后一步必为max节点，min节点是不会有move操作的，所以直接返回nullreturn { move: null, score: alpha, positions: positions, cutoffs: cutoffs };}}}
//计算到最好返回这些计算的值return { move: bestMove, score: bestScore, positions: positions, cutoffs: cutoffs };
}// performs a search and returns the best move
AI.prototype.getBest = function() {return this.iterativeDeep();
}// performs iterative deepening over the alpha-beta search
AI.prototype.iterativeDeep = function() {var start = (new Date()).getTime();var depth = 0;var best;//没有规定固定的depth 而是规定了计算时间，在规定时间内能计算到的深度do {var newBest = this.search(depth, -10000, 10000, 0 ,0);if (newBest.move == -1) {break;} else {best = newBest;}depth++;} while ( (new Date()).getTime() - start < minSearchTime);return best
}AI.prototype.translate = function(move) {return {0: 'up',1: 'right',2: 'down',3: 'left'}[move];
}

以上就是根据我的理解所做的注释，供大家参考如果有错误请大家指正！