public Simulator()
{
Population = new Dictionary<int, Chromosome>();
Scores = new Dictionary<int, int>();
Trace.WriteLine("Sim setting up, creating " + PopulationSize + " genomes.");
Random = new Random((int)DateTime.Now.Ticks % Int32.MaxValue);
for (int i = 0; i < PopulationSize; i++)
{
var c = new Chromosome(Chromosome.CreateOriginAction());
var cond = c.CreateConditional();
cond.Success = c.CreateAction();
cond.Failure = c.CreateAction();
c.Genome.AddChild(cond);
Population.Add(c.GetHashCode(), c);
}
Trace.WriteLine("Sim simulator ready to go.");
}
public void DoRun(Chromosome DNA, int RunLength)
{
ResetState();
var runStart = DateTime.Now.Ticks;
while ( DateTime.Now.Ticks - runStart < RunLength)
{
var actions = DNA.Enumerate(State).ToList();
Trace.Write("Emu got "+actions.Count()+" actions for this tick. Applying...");
foreach (var action in actions.OfType<Action>())
{
//write action's angles to state
foreach (var kv in action.Angles)
State[kv.Key] = kv.Value;
//upload the new state to the device
UpdateState(State);
//wait for the actions to complete
var start = DateTime.Now.Ticks;
while (!ReadState().SequenceEqual(State) && DateTime.Now.Ticks- start < ActionCompletionTimeout) ;
}
Trace.WriteLine(" done");
}
}
protected int JudgeFitness(Chromosome g)
{
//run simulation
var robot = new Robot();
robot.DoRun(g, RunLength);
//judge score
var gyro = robot.GetGyroState();
var tilt = Math.Abs(gyro[0]) + Math.Abs(gyro[1]);
if (tilt < 1) //floor tilt at 1 so there arn't DbZ issues
tilt = 1;
//we're trying to judge closeness to 0 for the x and y but height for z also encourage smalller programs
var score = (100 / tilt) * gyro[2] / g.Enumerate().Count();
Trace.WriteLine(String.Format("Run ended, judging fitness for " + g + " Gyro state: {0}, {1}, {2}. Score: {3}", gyro[0], gyro[1], gyro[2], score));
return score;
}
/// <summary>
/// Creates and returns a mutated version of this chromosome
/// </summary>
/// <param name="MutatePercentChance">The percentage chance that any given node in the chromosome will be modified</param>
/// <returns></returns>
public Chromosome Mutate(int MutatePercentChance)
{
var c = new Chromosome(Genome.Clone() as Node);
var nodes = c.Enumerate().ToList();
Trace.Write("Mutating: ");
foreach (var n in nodes)
{
if (Random.Next(100) < MutatePercentChance)
{
//can add a child
if (Random.Next(100) < MutateChanceAdd && nodes.Count < MutateMaxSize)
{
Trace.Write(" add ");
n.AddChild(CreateNode());
}
//can lose a child
if ((Random.Next(100) < MutateChanceLose && nodes.Count > MutateMinSize) || nodes.Count > MutateMaxSize)
{
Trace.Write(" rem ");
if (n.Children.Count > 0)
n.RemoveChild(n.Children[Random.Next(n.Children.Count)]);
}
//can change an action (this is like add and lose) or a functor
if (Random.Next(100) < MutateChanceMutate)
{
Trace.Write(" mut ");
var a = n as Action;
if (a != null)
Mutate(a);
else
{
var co = n as Conditional;
if (co != null)
Mutate(co);
}
//n.GetType().GetMethod("Mutate").Invoke(n, null);
}
}
}
Trace.WriteLine("");
return c;
}
/// <summary>
/// Swaps a random subtree in this chromosome with a random subtree in the partner one. won't modify the chromosome if nodes <= 1
/// </summary>
/// <param name="partner"></param>
public Chromosome[] Crossover(Chromosome partner)
{
var child1 = this.Clone() as Chromosome;
var child2 = partner.Clone() as Chromosome;
var nodes1 = child1.Enumerate().Count();
var nodes2 = child2.Enumerate().Count();
Node parent1 = null, parent2 = null;
while (parent1 == null && parent2 == null && nodes1 > 1 && nodes2 > 1)
{
var child1Site = child1.Enumerate().ElementAt(Random.Next(nodes1));
var child2Site = child2.Enumerate().ElementAt(Random.Next(nodes2));
parent1 = child1.Enumerate().FirstOrDefault(n => n.Children.Contains(child1Site));
parent2 = child2.Enumerate().FirstOrDefault(n => n.Children.Contains(child2Site));
if (parent1 != null && parent2 != null) //can't be crossing over root nodes!
{
parent1.AddChild(child2Site, parent1.Children.IndexOf(child1Site));
parent2.AddChild(child1Site, parent2.Children.IndexOf(child2Site));
parent1.RemoveChild(child1Site);
parent2.RemoveChild(child2Site);
}
}
return new Chromosome[] { child1, child2 };
}
public object Clone()
{
var c = new Chromosome(Genome.Clone() as Node);
return c;
}