// Use this for initialization
void Start()
{
tutorial_active = false;
source = GetComponent <AudioSource>();
initial_node = nodeManager.GetCurrentNode();
next_node = nodeManager.GetNextNode();
evo_controller = GetComponent <EvolutionController>();
transform.position = initial_node.transform.position;
initial_position = initial_node.transform.position;
next_position = next_node.transform.position;
//Update Arrow direction
target_controller.SetTarget(next_node.transform);
//Set camera at the initial position
camera_go.GetComponent <CameraController>().MoveCamera(transform);
//Reset HUD
DisablePowerUpHUD(PoweUpType.METAL);
DisablePowerUpHUD(PoweUpType.SLOW);
DisablePowerUpHUD(PoweUpType.STAR);
script_star.GetComponent <ScrollingUVs_Layers>().enabled = false;
if (startGame)
{
UI_Menu.GetComponent <UI_Game>().PlayGame();
}
}
public void TestMethod2()
{
var controller = new EvolutionController();
var response = controller.GetByID("x", 1, 1, 0, 1, 75);
Assert.IsTrue(response.result > 0);
}
void Awake()
{
Application.targetFrameRate = 60;
Time.timeScale = 1;
players = new List <PlayerMode>(11);
terrains = new Dictionary <TerrainPosition, TerrainGeneration>();
particles = new List <ParticleSystem>(11);
cam = Camera.main.GetComponent <CameraFollow>();
evolutionManager = GetComponent <EvolutionController>();
tests = 0;
}
/// <summary>
/// Adds the agent to the team if requested.
/// </summary>
private void Start()
{
if (m_AddToTeam)
{
TeamManager.AddTeamMember(gameObject, m_TeamIndex);
}
// Genetic Algorithm initialize
evolver = GameObject.Find("Evolution Controller").GetComponent <EvolutionController>();
playerName = this.gameObject.name;
phenoType = evolver.GetPhenoType(playerName);
}
public void Start()
{
if (EvolutionControler == null)
{
Debug.Log("EvolutionController not set - trying to get it from this gameObject.");
EvolutionControler = GetComponent <EvolutionController>(); if (EvolutionControler == null)
{
Debug.LogError("EvolutionController still not set! Disableing.");
enabled = false;
return;
}
return;
}
}
// Use this for initialization
void Start()
{
myTimers = this.GetComponent <Timers>();
myMovement = this.GetComponent <Movement>();
myAnimator = this.GetComponent <Animator>();
myImage = this.GetComponent <Image>();
myAnimController = this.GetComponent <AnimationController>();
myEvolutionController = this.GetComponent <EvolutionController>();
ExpRequirements = new int[6] {
10, 20, 30, 40, 50, 60
}; //to be defined in json in future
uiValues = new List <string>()
{
m_name, m_hunger.ToString(), m_experience.ToString()
};
}
// Use this for initialization
void Start()
{
Screen.SetResolution(80, 80, false);
Application.targetFrameRate = 15;
evolver = GameObject.Find("Evolution Controller").GetComponent <EvolutionController>();
evoManager = new EvolutionInfoManager();
evoManager.ReadInfo();
if (evoManager.Initial())
{
// The first game of the first iteration
evoManager.Population = evolver.InitializeRandomPopulation(evoManager.N);
evoManager.InitializePopulationQueue();
evoManager.WritePopulation("population.csv");
}
else if (evoManager.SelectBest())
{
evoManager.ReadPopulation("population.csv");
List <PhenoType> best = Selection();
evoManager.Population = best;
evoManager.WritePopulation("prev-population.csv");
evoManager.ChildPopulation = GenerateOffspring();
evoManager.Population = evoManager.ChildPopulation;
evoManager.InitializePopulationQueue();
}
else if (evoManager.EvaluateOffspring())
{
evoManager.ReadPopulation("population.csv");
evoManager.WritePopulation("prev-population.csv");
evoManager.ChildPopulation = GenerateOffspring();
evoManager.Population = evoManager.ChildPopulation;
evoManager.InitializePopulationQueue();
}
else
{
evoManager.ReadPopulation("population.csv");
evoManager.ReadPopulationQueue();
}
PlayGame();
}
static void TestGeneticAlgorithm()
{
string target = "Be or not to be?";
IEvolutionController evolutionController = new EvolutionController(target);
Population population = new Population(evolutionController, 300);
population.MutationChance = 10;
population.CurrentGeneration.Evaluate();
while (true)
{
ReadKey();
population.CurrentGeneration.Evaluate();
IDna db = population.CurrentGeneration.Best;
WriteLine(new string(db.GetGenes() as char[]) + " ||| " + db.Fitness);
population.CreateNewGeneration();
}
}
bool[] reachedMarker; //if a particular marker has been reached, true. Same order and size as goalmarkers
// Use this for initialization
void Start()
{
rb = GetComponent <Rigidbody2D>();
rand = new System.Random(Guid.NewGuid().GetHashCode());
initialPos = transform.position;
ec = GameObject.Find("EvolutionController").GetComponent <EvolutionController>();
//initialize square with ec data
maxSteps = ec.GetCurrMaxSteps();
mutationRate = ec.GetMutationRate();
currStep = 0;
currDelay = 0;
//get initial list of movements
//if not a square loaded from disk
if (!loadedSquare)
{
InitializeMovements();
}
}
void Update()
{
if (Input.GetButtonUp("AI_ON"))
{
AIEnablied = true;
brain = EvolutionController.CreateNeuralNet(evaluator);
brain.setWeights(new Queue <double>(generateRandomWeights(brain.extractWeights().Count)));
}
if (AIEnablied)
{
setNeuralInputs();
List <double> output = brain.calculateOutput();
for (int i = 0; i < output.Count; ++i)
{
float newThrottle = output[i] < 0 ? 0 : (float)output[i];
if (newThrottle > 1.0f)
{
newThrottle = 1.0f;
}
thrusterControllers[i].throttle = newThrottle;
}
}
else
{
// if (Input.GetButton("Jump")) {
// foreach (ThrusterController thrusterController in thrusterControllers) {
// thrusterController.firing = true;
// }
// } else {
// foreach (ThrusterController thrusterController in thrusterControllers) {
// thrusterController.firing = false;
// }
// }
}
}
// Use this for initialization
void Start()
{
ec = GameObject.Find("EvolutionController").GetComponent <EvolutionController>();
stepsText = this.GetComponent <Text>();
}
// Use this for initialization
void Start()
{
text = transform.GetChild(0).GetComponent <Text>();
ec = GameObject.Find("EvolutionController").GetComponent <EvolutionController>();
}
