--- a/ai.js Fri Jul 03 22:21:05 2015 -0500
+++ b/ai.js Fri Jul 03 22:31:58 2015 -0500
@@ -184,13 +184,13 @@
////////////////////////////////////////////////////////////////
-// 1 step deep with linear weight function on score, max value,
+// 1 step deep with linear utility function on score, max value,
// bonuses for max value stay at corner or edge and bonuses
// for each free field.
////////////////////////////////////////////////////////////////
/**
- * Defines coefficient for linear resulted weight function.
+ * Defines coefficient for linear resulted utility function.
* @name ai.OneStepAhead.cfg
* @namespace
* @property {number} scoreCoef multiplicator for score
@@ -210,34 +210,34 @@
ai.copyObj(cfg, this.cfg);
}
ai.OneStepAhead.bestCfg = {scoreCoef: 1, maxValCoef: 0, cornerBonus: 0, edgeBonus: 0, freeBonus: 0};
-ai.OneStepAhead.prototype.weight = function(brd) {
- var weight = 0;
+ai.OneStepAhead.prototype.utility = function(brd) {
+ var utility = 0;
if (this.cfg.scoreCoef > 0)
- weight += this.cfg.scoreCoef * brd.score();
+ utility += this.cfg.scoreCoef * brd.score();
var max = brd.maxVal();
if (this.cfg.maxValCoef > 0)
- weight += this.cfg.maxValCoef * max;
+ utility += this.cfg.maxValCoef * max;
if (this.cfg.cornerBonus > 0 && brd.atCorner(max))
- weight += this.cfg.cornerBonus;
+ utility += this.cfg.cornerBonus;
if (this.cfg.edgeBonus > 0 && brd.atEdge(max))
- weight += this.cfg.edgeBonus;
+ utility += this.cfg.edgeBonus;
if (this.cfg.freeBonus > 0)
- weight += this.cfg.freeBonus * brd.freeCnt();
- return weight;
+ utility += this.cfg.freeBonus * brd.freeCnt();
+ return utility;
}
/** Select best direction for next step. */
ai.OneStepAhead.prototype.analyse = function(brd2d) {
var origBrd = new this.brd(brd2d);
var nextBrd = new this.brd();
- var maxWeight = -1;
+ var maxUtility = -1;
var bestDir;
for (var i = 0; i < ai.dirs.length; i++) {
var dir = ai.dirs[i];
if (origBrd[dir](nextBrd)) {
- var weight = this.weight(nextBrd);
- if (maxWeight < weight) {
+ var utility = this.utility(nextBrd);
+ if (maxUtility < utility) {
bestDir = dir;
- maxWeight = weight;
+ maxUtility = utility;
}
}
}
@@ -253,7 +253,7 @@
////////////////////////////////////////////////////////////////
/**
- * Defines coefficient for linear resulted weight function.
+ * Defines coefficient for linear resulted utility function.
* @name ai.StaticDeepMerges.cfg
* @namespace
* @property {number} scoreCoef multiplicator for score
@@ -272,41 +272,41 @@
this.cfg = ai.copyObj(ai.OneStepAhead.bestCfg);
ai.copyObj(cfg, this.cfg);
}
-ai.StaticDeepMerges.bestCfg = {scoreCoef: 1, maxValCoef: 0, cornerBonus: 0, edgeBonus: 0, freeBonus: 0, weightThreshold: 10};
-ai.StaticDeepMerges.prototype.weight = function(brd) {
- var weight = 0;
+ai.StaticDeepMerges.bestCfg = {scoreCoef: 1, maxValCoef: 0, cornerBonus: 0, edgeBonus: 0, freeBonus: 0, utilityThreshold: 10};
+ai.StaticDeepMerges.prototype.utility = function(brd) {
+ var utility = 0;
if (this.cfg.scoreCoef > 0)
- weight += this.cfg.scoreCoef * brd.score();
+ utility += this.cfg.scoreCoef * brd.score();
var max = brd.maxVal();
if (this.cfg.maxValCoef > 0)
- weight += this.cfg.maxValCoef * max;
+ utility += this.cfg.maxValCoef * max;
if (this.cfg.cornerBonus > 0 && brd.atCorner(max))
- weight += this.cfg.cornerBonus;
+ utility += this.cfg.cornerBonus;
if (this.cfg.edgeBonus > 0 && brd.atEdge(max))
- weight += this.cfg.edgeBonus;
+ utility += this.cfg.edgeBonus;
if (this.cfg.freeBonus > 0)
- weight += this.cfg.freeBonus * brd.freeCnt();
- return weight;
+ utility += this.cfg.freeBonus * brd.freeCnt();
+ return utility;
}
/** Select best direction for next step. */
ai.StaticDeepMerges.prototype.analyse = function(brd2d) {
var origBrd = new this.brd(brd2d);
var nextBrd = new this.brd();
var prevScore = -1, nextScore = -1;
- var maxWeight = -1;
+ var maxUtility = -1;
var bestDir;
for (var i = 0; i < ai.dirs.length; i++) {
var dir = ai.dirs[i];
if (origBrd[dir](nextBrd)) {
- var weight = this.evalFn(nextBrd);
- var ok = (weight - maxWeight) > this.cfg.weightThreshold;
- if ( ! ok && maxWeight <= weight) {
- nextScore = this.weight(nextBrd);
+ var utility = this.evalFn(nextBrd);
+ var ok = (utility - maxUtility) > this.cfg.utilityThreshold;
+ if ( ! ok && maxUtility <= utility) {
+ nextScore = this.utility(nextBrd);
ok = prevScore < nextScore;
}
if (ok) {
prevScore = nextScore;
- maxWeight = weight;
+ maxUtility = utility;
bestDir = dir;
}
}
@@ -315,16 +315,16 @@
}
ai.StaticDeepMerges.prototype.evalFn = function(brd) {
var currScore = brd.score();
- var maxWeight = currScore;
+ var maxUtility = currScore;
var nextBrd = new this.brd();
for (var i = 0; i < ai.dirs.length; i++) {
if (brd[ai.dirs[i]](nextBrd)) {
var score = nextBrd.score();
if (score > currScore)
- maxWeight = Math.max(maxWeight, this.evalFn(nextBrd));
+ maxUtility = Math.max(maxUtility, this.evalFn(nextBrd));
}
}
- return maxWeight;
+ return maxUtility;
}
/* Mark that next board will be unrelated to previous, so any stored precompution can be cleared. */
ai.StaticDeepMerges.prototype.cleanup = function() { }
@@ -336,7 +336,7 @@
////////////////////////////////////////////////////////////////
/**
- * Defines coefficient for linear resulted weight function.
+ * Defines coefficient for linear resulted utility function.
* @name ai.expectimax.cfg
* @namespace
* @property {number} scoreCoef multiplicator for score
@@ -362,7 +362,7 @@
this.cfg.depth = ai.expectimax.bestCfg.depth;
}
ai.expectimax.bestCfg = {balance: .9, depth: 5, scoreCoef: 1, maxValCoef: 0, cornerBonus: 0, edgeBonus: 0, freeBonus: 0};
-ai.expectimax.prototype.weight = function(brd) {
+ai.expectimax.prototype.utility = function(brd) {
var score = 0;
var cfg = this.cfg;
if (cfg.scoreCoef > 0)
@@ -409,7 +409,7 @@
}
ai.expectimax.prototype.evalFn = function(brd, depth) {
if (depth >= this.depthLimit)
- return this.weight(brd);
+ return this.utility(brd);
var wCached = this.brdCache.get(brd);
if (wCached)
return wCached;
@@ -453,7 +453,7 @@
////////////////////////////////////////////////////////////////
/**
- * Defines coefficient for linear resulted weight function.
+ * Defines coefficient for linear resulted utility function.
* @name ai.survive.cfg
* @namespace
* @property {number} scoreCoef multiplicator for score
@@ -478,7 +478,7 @@
this.cfg.altAI = new ai.StaticDeepMerges(brd, ai.survive.altAICfg);
}
ai.survive.bestCfg = {freeCells: 8, maxDepth: 5};
-ai.survive.altAICfg = {scoreCoef: 1, maxValCoef: 0, cornerBonus: 0, edgeBonus: 0, freeBonus: 0, weightThreshold: 0};
+ai.survive.altAICfg = {scoreCoef: 1, maxValCoef: 0, cornerBonus: 0, edgeBonus: 0, freeBonus: 0, utilityThreshold: 0};
/** Select best direction for next step. */
ai.survive.prototype.analyse = function(brd2d) {
var origBrd = new this.brd(brd2d);
@@ -573,19 +573,19 @@
ai.MonteCarlo.prototype.analyse = function(brd2d) {
var origBrd = new this.brd(brd2d);
var nextBrd = new this.brd();
- var bestW = - this.cfg.simulations;
+ var bestUtility = - this.cfg.simulations;
var bestDir;
var freeCnt = origBrd.freeCnt();
for (var i = 0; i < ai.dirs.length; i++) {
var dir = ai.dirs[i];
if (origBrd[dir](nextBrd)) {
- var w = 0;
+ var utility = 0;
for (var gameCnt = this.cfg.simulations; gameCnt > 0; gameCnt--) {
var tmpBrd = nextBrd.copy();
- w += this.play(tmpBrd, this.cfg.maxDepth);
+ utility += this.play(tmpBrd, this.cfg.maxDepth);
}
- if (w > bestW) {
- bestW = w;
+ if (utility > bestUtility) {
+ bestUtility = utility;
bestDir = dir;
}
}
@@ -608,17 +608,17 @@
return -1;
}
ai.MonteCarlo.prototype.evalFn = function(brd) {
- var w = 0;
+ var utility = 0;
if (this.cfg.freeBonus > 0)
- w += this.cfg.freeBonus * brd.freeCnt();
+ utility += this.cfg.freeBonus * brd.freeCnt();
var max = brd.maxVal();
if (max > 7) {
if (this.cfg.cornerBonus > 0 && brd.atCorner(max))
- w += this.cfg.cornerBonus;
+ utility += this.cfg.cornerBonus;
if (this.cfg.edgeBonus > 0 && brd.atEdge(max))
- w += this.cfg.edgeBonus;
+ utility += this.cfg.edgeBonus;
}
- return w;
+ return utility;
}
/* Mark that next board will be unrelated to previous, so any stored precompution can be cleared. */
ai.MonteCarlo.prototype.cleanup = function() {