private void GenomesToAcceptability(IList <TGenome> genomeList)
{
string TEMP_NETWORK_FILE = string.Format("____temp{0}____network.xml", TrialId);
var neatGenomeParams = new NeatGenomeParameters()
{
ActivationFn = PlainSigmoid.__DefaultInstance,
InitialInterconnectionsProportion = 1
};
int inputs = _world.PlantTypes.Count() * World.SENSORS_PER_OBJECT_TYPE
+ _world.Predators.Count() * World.SENSORS_PER_OBJECT_TYPE
+ 1;
int outputs = 2;
var factory = new NeatGenomeFactory(inputs, outputs, neatGenomeParams);
for (int i = 0; i < _agents.Length; i++)
{
// Decode the genome.
IBlackBox phenome = _genomeDecoder.Decode(genomeList[i]);
IAcceptabilityFunction accept = new RecurrentNeuralAcceptability(phenome);
// Check that the genome is valid.
if (phenome == null)
{
Console.WriteLine("Couldn't decode genome {0}!", i);
_agents[i] = new SpinningAgent(i);
continue;
}
// Create a feed forward network with 10 hidden nodes and random weights
SocialExperiment.CreateNetwork(TEMP_NETWORK_FILE, inputs, outputs);
using (var xr = XmlReader.Create(TEMP_NETWORK_FILE))
{
var controllerGenome = NeatGenomeXmlIO.ReadCompleteGenomeList(xr, false, factory)[0];
var controllerPhenome = _genomeDecoder.Decode((TGenome)controllerGenome);
_agents[i] = new SocialAgent(i, _genomeList[i].SpecieIdx, controllerPhenome, _agentsNavigate, _agentsHide, accept)
{
MemorySize = CurrentMemorySize
};
var network = (FastCyclicNetwork)controllerPhenome;
network.Momentum = ((SocialAgent)_agents[i]).Momentum;
network.BackpropLearningRate = ((SocialAgent)_agents[i]).LearningRate;
}
}
File.Delete(TEMP_NETWORK_FILE);
}
private void GenomesToPolicies(IList <TGenome> genomeList)
{
for (int i = 0; i < _agents.Length; i++)
{
// Decode the genome.
IBlackBox phenome = _genomeDecoder.Decode(genomeList[i]);
// Check that the genome is valid.
if (phenome == null)
{
Console.WriteLine("Couldn't decode genome {0}!", i);
_agents[i] = new SpinningAgent(i);
}
else
{
_agents[i] = getAgent(i, phenome);
}
}
}
