# HG changeset patch
# User Oleksandr Gavenko <gavenkoa@gmail.com>
# Date 1435035590 18000
# Node ID ae123e309e3199fbc4ec495ec343bdae2562c094
# Parent  4579c59e7e6b797eda799ac4fc9e6adbdf1c6b5b
Refactoring: rename "weight" to "utility".

diff -r 4579c59e7e6b -r ae123e309e31 2048.html
--- a/2048.html	Wed Jun 10 21:57:38 2015 -0500
+++ b/2048.html	Mon Jun 22 23:59:50 2015 -0500
@@ -253,7 +253,7 @@
           <input type="text" name="freeBonus" class="positive" pattern="[0-9]*[.]?[0-9]*" value="10"/> free cell coefficient
         </div>
         <div class="option">
-          <input type="text" name="weightThreshold" class="positive" pattern="[0-9]*[.]?[0-9]*" value="10"/> score threshold
+          <input type="text" name="utilityThreshold" class="positive" pattern="[0-9]*[.]?[0-9]*" value="10"/> score threshold
         </div>
       </div>
       <div class="ai wide control" id="ai-expectimax">
diff -r 4579c59e7e6b -r ae123e309e31 ai.js
--- a/ai.js	Wed Jun 10 21:57:38 2015 -0500
+++ b/ai.js	Mon Jun 22 23:59:50 2015 -0500
@@ -173,13 +173,13 @@
 
 
 ////////////////////////////////////////////////////////////////
-// 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
@@ -199,34 +199,34 @@
     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.brdEngine(brd2d);
     var nextBrd = new this.brdEngine();
-    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;
             }
         }
     }
@@ -242,7 +242,7 @@
 ////////////////////////////////////////////////////////////////
 
 /**
- * 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
@@ -261,41 +261,41 @@
     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.brdEngine(brd2d);
     var nextBrd = new this.brdEngine();
     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;
             }
         }
@@ -304,16 +304,16 @@
 }
 ai.StaticDeepMerges.prototype.evalFn = function(brd) {
     var currScore = brd.score();
-    var maxWeight = currScore;
+    var maxUtility = currScore;
     var nextBrd = new this.brdEngine();
     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() { }
@@ -325,7 +325,7 @@
 ////////////////////////////////////////////////////////////////
 
 /**
- * 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
@@ -351,7 +351,7 @@
         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)
@@ -398,7 +398,7 @@
 }
 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;
@@ -442,7 +442,7 @@
 ////////////////////////////////////////////////////////////////
 
 /**
- * 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
@@ -467,7 +467,7 @@
     this.cfg.altAI = new ai.StaticDeepMerges(brdEngine, 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.brdEngine(brd2d);