Added Lunar Lander example and fixed small issue with GA compareTo an…

…d Equals (from a bug found in Java)

ConsoleExamples/ConsoleExamples.cs

@@ -39,6 +39,7 @@
 using Encog.Examples.Hopfield.Simple;
 using Encog.Examples.Image;
 using Encog.Examples.JordanNetwork;
+using Encog.Examples.Lunar;
 using Encog.Examples.Market;
 using Encog.Examples.Persist;
 using Encog.Examples.XOR;
@@ -88,6 +89,7 @@ public ConsoleExamples()
             examples.Add(ForestCover.Info);
             examples.Add(Encog.Examples.Market.MarketPredict.Info);
             examples.Add(CSVMarketExample.Info);
+            examples.Add(LunarLander.Info);
         }
 
         public void ListCommands()

ConsoleExamples/ConsoleExamples.csproj

@@ -72,6 +72,10 @@
     <Compile Include="Examples\Image\ImageNeuralNetwork.cs" />
     <Compile Include="Examples\Image\ImagePair.cs" />
     <Compile Include="Examples\JordanNetwork\JordanExample.cs" />
+    <Compile Include="Examples\Lunar\LanderSimulator.cs" />
+    <Compile Include="Examples\Lunar\LunarLander.cs" />
+    <Compile Include="Examples\Lunar\NeuralPilot.cs" />
+    <Compile Include="Examples\Lunar\PilotScore.cs" />
     <Compile Include="Examples\Market\Config.cs" />
     <Compile Include="Examples\Market\MarketBuildTraining.cs" />
     <Compile Include="Examples\Market\MarketEvaluate.cs" />

ConsoleExamples/ConsoleExamples.csproj.user

@@ -1,9 +1,9 @@
 <?xml version="1.0" encoding="utf-8"?>
 <Project xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
   <PropertyGroup Condition=" '$(Configuration)|$(Platform)' == 'Debug|AnyCPU' ">
-    <StartArguments>Tests</StartArguments>
+    <StartArguments>-pause lander</StartArguments>
   </PropertyGroup>
   <PropertyGroup Condition=" '$(Configuration)|$(Platform)' == 'Release|AnyCPU' ">
-    <StartArguments>-pause forest evaluate</StartArguments>
+    <StartArguments>-pause lander</StartArguments>
   </PropertyGroup>
 </Project>

ConsoleExamples/Examples/Lunar/LanderSimulator.cs

@@ -0,0 +1,70 @@
+using System;
+using System.Text;
+using Encog.Util;
+
+namespace Encog.Examples.Lunar
+{
+    public class LanderSimulator
+    {
+        public const double Gravity = 1.62;
+        public const double Thrust = 10;
+        public const double TerminalVelocity = 40;
+
+        public LanderSimulator()
+        {
+            Fuel = 200;
+            Seconds = 0;
+            Altitude = 10000;
+            Velocity = 0;
+        }
+
+        public int Fuel { get; set; }
+        public int Seconds { get; set; }
+        public double Altitude { get; set; }
+        public double Velocity { get; set; }
+
+        public int Score
+        {
+            get { return (int) ((Fuel*10) + Seconds + (Velocity*1000)); }
+        }
+
+        public void Turn(bool thrust)
+        {
+            Seconds++;
+            Velocity -= Gravity;
+            Altitude += Velocity;
+
+            if (thrust && Fuel > 0)
+            {
+                Fuel--;
+                Velocity += Thrust;
+            }
+
+            Velocity = Math.Max(-TerminalVelocity, Velocity);
+            Velocity = Math.Min(TerminalVelocity, Velocity);
+
+            if (Altitude < 0)
+                Altitude = 0;
+        }
+
+        public String Telemetry()
+        {
+            var result = new StringBuilder();
+            result.Append("Elapsed: ");
+            result.Append(Seconds);
+            result.Append(" s, Fuel: ");
+            result.Append(Fuel);
+            result.Append(" l, Velocity: ");
+            result.Append(Format.FormatDouble(Velocity, 4));
+            result.Append(" m/s, ");
+            result.Append((int) Altitude);
+            result.Append(" m");
+            return result.ToString();
+        }
+
+        public bool Flying
+        {
+            get { return Altitude > 0; }
+        }
+    }
+}

ConsoleExamples/Examples/Lunar/LunarLander.cs

@@ -0,0 +1,90 @@
+using System;
+using ConsoleExamples.Examples;
+using Encog.Engine.Network.Activation;
+using Encog.Mathutil.Randomize;
+using Encog.ML.Train;
+using Encog.Neural.Networks;
+using Encog.Neural.Networks.Training.Anneal;
+using Encog.Neural.Networks.Training.Genetic;
+using Encog.Neural.Pattern;
+
+namespace Encog.Examples.Lunar
+{
+    /// <summary>
+    /// A lunar lander game where the neural network learns to land a space craft.  
+    /// The neural network learns the proper amount of thrust to land softly 
+    /// and conserve fuel.
+    /// 
+    /// This example is unique because it uses supervised training, yet does not 
+    /// have expected values.  For this it can use genetic algorithms or 
+    /// simulated annealing.
+    /// </summary>
+    public class LunarLander : IExample
+    {
+        public static ExampleInfo Info
+        {
+            get
+            {
+                var info = new ExampleInfo(
+                    typeof(LunarLander),
+                    "lander",
+                    "Train a neural network to land a space ship.",
+                    "This example uses a genetic algorithm to land a space craft on the moon.  No training data is given, but it uses supervised training to land.");
+                return info;
+            }
+        }
+
+        #region IExample Members
+
+        /// <summary>
+        /// Program entry point.
+        /// </summary>
+        /// <param name="app">Holds arguments and other info.</param>
+        public void Execute(IExampleInterface app)
+        {
+            BasicNetwork network = CreateNetwork();
+
+            IMLTrain train;
+
+            if (app.Args.Length > 0 && String.Compare(app.Args[0], "anneal", true) == 0)
+            {
+                train = new NeuralSimulatedAnnealing(
+                    network, new PilotScore(), 10, 2, 100);
+            }
+            else
+            {
+                train = new NeuralGeneticAlgorithm(
+                    network, new FanInRandomizer(),
+                    new PilotScore(), 500, 0.1, 0.25);
+            }
+
+            int epoch = 1;
+
+            for (int i = 0; i < 50; i++)
+            {
+                train.Iteration();
+                Console.WriteLine(@"Epoch #" + epoch + @" Score:" + train.Error);
+                epoch++;
+            }
+
+            Console.WriteLine(@"\nHow the winning network landed:");
+            network = (BasicNetwork) train.Method;
+            var pilot = new NeuralPilot(network, true);
+            Console.WriteLine(pilot.ScorePilot());
+            EncogFramework.Instance.Shutdown();
+        }
+
+        #endregion
+
+        public static BasicNetwork CreateNetwork()
+        {
+            var pattern = new FeedForwardPattern {InputNeurons = 3};
+            pattern.AddHiddenLayer(50);
+            pattern.OutputNeurons = 1;
+            pattern.ActivationFunction = new ActivationTANH();
+            var network = (BasicNetwork) pattern.Generate();
+            network.Reset();
+            return network;
+        }
+    }
+}

ConsoleExamples/Examples/Lunar/NeuralPilot.cs

@@ -0,0 +1,59 @@
+using System;
+using Encog.ML.Data;
+using Encog.ML.Data.Basic;
+using Encog.Neural.Networks;
+using Encog.Util.Arrayutil;
+
+namespace Encog.Examples.Lunar
+{
+    public class NeuralPilot
+    {
+        private readonly NormalizedField _fuelStats;
+        private readonly BasicNetwork _network;
+        private readonly bool _track;
+        private readonly NormalizedField _altitudeStats;
+        private readonly NormalizedField _velocityStats;
+
+        public NeuralPilot(BasicNetwork network, bool track)
+        {
+            _fuelStats = new NormalizedField(NormalizationAction.Normalize, "fuel", 200, 0, -0.9, 0.9);
+            _altitudeStats = new NormalizedField(NormalizationAction.Normalize, "altitude", 10000, 0, -0.9, 0.9);
+            _velocityStats = new NormalizedField(NormalizationAction.Normalize, "velocity",
+                                                LanderSimulator.TerminalVelocity, -LanderSimulator.TerminalVelocity,
+                                                -0.9, 0.9);
+
+            _track = track;
+            _network = network;
+        }
+
+        public int ScorePilot()
+        {
+            var sim = new LanderSimulator();
+            while (sim.Flying)
+            {
+                IMLData input = new BasicMLData(3);
+                input[0] = _fuelStats.Normalize(sim.Fuel);
+                input[1] = _altitudeStats.Normalize(sim.Altitude);
+                input[2] = _velocityStats.Normalize(sim.Velocity);
+                IMLData output = _network.Compute(input);
+                double value = output[0];
+
+                bool thrust;
+
+                if (value > 0)
+                {
+                    thrust = true;
+                    if (_track)
+                        Console.WriteLine(@"THRUST");
+                }
+                else
+                    thrust = false;
+
+                sim.Turn(thrust);
+                if (_track)
+                    Console.WriteLine(sim.Telemetry());
+            }
+            return (sim.Score);
+        }
+    }
+}

ConsoleExamples/Examples/Lunar/PilotScore.cs

@@ -0,0 +1,25 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using Encog.ML;
+using Encog.Neural.Networks;
+using Encog.Neural.Networks.Training;
+
+namespace Encog.Examples.Lunar
+{
+    public class PilotScore : ICalculateScore
+    {
+        public double CalculateScore(IMLRegression network)
+        {
+            NeuralPilot pilot = new NeuralPilot((BasicNetwork)network, false);
+            return pilot.ScorePilot();
+        }
+
+
+        public bool ShouldMinimize
+        {
+            get { return false; }
+        }
+    }
+}

EncogCmd/app.config

@@ -0,0 +1,3 @@
+<?xml version="1.0"?>
+<configuration>
+<startup><supportedRuntime version="v2.0.50727" sku="Client"/></startup></configuration>