Add .gitignore

.gitignore

@@ -0,0 +1 @@
+/build/neuralnetwork/storage/*

build/neuralnetwork/core/Genome.php

@@ -225,7 +225,7 @@
 		* @threshold<double> 									Mutation threshold
 		*
 		*/
-		public function mutation($threshold=0.5){
+		public function mutation($threshold=1){
 			/* (1) Checks @threshold argument */
 			if( floatval($threshold) !== $threshold || $threshold < 0 || $threshold > 1 )
 				throw new \Exception('Invalid threshold for Genome mutation.');
@@ -295,10 +295,15 @@
 							// echo "result:  ${neurons[$n]}\n\n";
 						}
 
+						if( $l == 1 )
+							$neurons[$n] /= $this->inputN;
+						else
+							$neurons[$n] /= $this->neurons;
 					}
 
 
 
+
 				}
 
 

build/neuralnetwork/core/NeuralNetworkCore.php

@@ -83,6 +83,9 @@
 				], 'ft' => [
 					'filename' => $absolute_path.'.ft', // will contain genomes' fitness
 					'exists'   => is_file($absolute_path.'.ft')
+				], 'ln' => [
+					'filename' => $absolute_path.'.ln', // will contain learnt best genomes
+					'exists'   => is_file($absolute_path.'.ln')
 				]
 			];
 
@@ -341,6 +344,61 @@
 
 		}
 
+		/* INITIALIZES THE LEARNING ROUTINE WITH LEARNT DATA AS THE FIRST GENOME
+		*
+		* @callback<Function> 									Callback function to display current state
+		*
+		*/
+		public function loadLearningRoutine($callback=null){
+			/* [1] Manages @callback argument
+			=========================================================*/
+			if( !is_callable($callback) ) $this->callback = function(){};
+			else                          $this->callback = $callback;
+
+			/* [2] Creates the First generation and serialize it
+			=========================================================*/
+			/* (1) Initializes data & storage */
+			$this->gnr = 0;
+			$this->gnm = 0;
+			FileManager::write($this->storage['gn']['filename'], '');
+			FileManager::write($this->storage['ft']['filename'], '');
+
+			/* (2) Fetch learnt best genomes */
+			$loadedGenomes = [
+				FileManager::readline($this->storage['ln']['filename'], 0),
+				FileManager::readline($this->storage['ln']['filename'], 1)
+			];
+
+			/* (3) Unserializes them */
+			$father = new Genome(2, 2, 2, 2);
+				$father->unserialize($loadedGenomes[0]);
+
+			$mother = new Genome(2, 2, 2, 2);
+				$mother->unserialize($loadedGenomes[1]);
+
+			/* (4) Create childrens */
+			for( $g = 0 ; $g < $this->maxGnm ; $g++ ){
+
+				// {6.1} Re-use father //
+				if( $g == 0 )
+					FileManager::append($this->storage['gn']['filename'], $father->serialize());
+
+				// {6.2} Re-use mother //
+				else if( $g == 1 )
+					FileManager::append($this->storage['gn']['filename'], $mother->serialize());
+
+				// {6.3} Do cross-over + mutation for the rest //
+				else{
+					$gnm = new Genome($father, $mother);
+					$gnm->mutation($this->mutThr);
+					FileManager::append($this->storage['gn']['filename'], $gnm->serialize());
+				}
+
+			}
+
+		}
+
+
 		/* RETURNS THE CURRENT GENOME
 		*
 		* @return genome<Genome>		 						Returns the current genome
@@ -441,8 +499,18 @@
 			/* (3) If end of process
 			---------------------------------------------------------*/
 			}else{
+
+				/* (1) Get the 2 best genomes */
+				$best = FileManager::readline($this->storage['ln']['filename'], 0);
+				$best.= FileManager::readline($this->storage['ln']['filename'], 1);
+
+				/* (2) Stores data to learnt data */
+				FileManager::write($this->storage['ln']['filename'], $best);
+
+				/* (3) Destroy cursors */
 				$this->gnr = null;
 				$this->gnm = null;
+
 			}
 		}
 
@@ -479,6 +547,10 @@
 				$c++;
 			}
 
+			/* (3) Anti-regression, if @mother < @father only use @father*/
+			if( $fitnesses[$iMother] < $fitnesses[$iFather] )
+				$iMother = $iFather;
+
 			return [ $iFather, $iMother ];
 		}
 

build/neuralnetwork/storage/test/test1.nn

@@ -1 +1 @@
-{"maxGnr":50,"maxGnm":1000,"kptGnm":2,"mutThr":0.3,"fitEnd":1,"numHid":2,"numNeu":3,"inpNeu":3,"outNeu":2,"storage":{"nn":{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.nn","exists":false},"ex":{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.ex","exists":false},"gn":{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.gn","exists":false},"ft":{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.ft","exists":false}}}
+{"maxGnr":50,"maxGnm":1000,"mutThr":0.5,"fitEnd":1,"numHid":4,"numNeu":4,"inpNeu":3,"outNeu":2,"storage":{"nn":{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.nn","exists":false},"ex":{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.ex","exists":false},"gn":{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.gn","exists":false},"ft":{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.ft","exists":false},"ln":{"filename":"\/home\/xdrm-brackets\/Desktop\/git.xdrm.io\/neural-network.php\/build\/neuralnetwork\/storage\/test\/test1.ln","exists":false}}}

config/neural-network.json

@@ -2,7 +2,7 @@
 	"storage_parent": "/build/neuralnetwork/storage",
 
 	"default": {
-		"mutation_threshold": 0.3,
+		"mutation_threshold": 0.5,
 		"fitness_end":        1,
 		"storage":            "_buffer",
 		"hidden_layers":      2,

public/main.php

@@ -32,9 +32,10 @@
 			$nn = NeuralNetwork::create(50, 1000);
 
 			$nn->setHiddenLayersCount(4);
-			$nn->setHiddenLayerNeuronsCount(3);
+			$nn->setHiddenLayerNeuronsCount(4);
 			$nn->setInputLayerCount(3);
 			$nn->setOutputLayerCount(2);
+			$nn->setMutationThreshold(0.5);
 
 			echo "$part. NeuralNetwork configured\n"; $part++;
 
@@ -66,10 +67,12 @@
 		=========================================================*/
 		$fitness = 0;
 		$max_fit = 0;
-		$nn->initLearningRoutine(function($input, $output){
+		$nn->loadLearningRoutine(function($input, $output){
 			global $fitness;
-			if( $output[0] == behaviour($input)[0] ) $fitness++;
+			$diff = [ abs($output[0] - behaviour($input)[0]), abs($output[1] - behaviour($input)[1]) ];
-			if( $output[1] == behaviour($input)[1] ) $fitness++;
+
+			if( $diff[0] > 0 ) $fitness += 1 / $diff[0];
+			if( $diff[1] > 0 ) $fitness += 1 / $diff[1];
 		});
 		echo "$part. Learning routine initialized.\n"; $part++;
 
@@ -79,6 +82,9 @@
 		/* (1) For each generation */
 		for( $gnr = 0 ; $gnr < 50 ; $gnr++ ){
 
+			$max_fit = 0;
+			$start = microtime(true);
+
 			/* (2) For each genome */
 			for( $gnm = 0 ; $gnm < 1000 ; $gnm++ ){
 				$fitness = 0;
@@ -98,6 +104,8 @@
 				$nn->nextGenome();
 			}
 
+			echo "\n\t".((microtime(true)-$start))."s\n";
+
 		}