/// <summary>
/// DeepCopy Constructor
/// </summary>
/// <param name="agent">NN to DeepCopy</param>
public NNAgent(NNAgent agent)
{
// DeepCopy of Layers of this NN
layers = new int[agent.layers.Length];
for (int i = 0; i < agent.layers.Length; i++)
{
layers[i] = agent.layers[i];
}
bias = agent.bias;
// Generate Matrix
InitNeurons();
InitWeights();
// Set Weights
CopyWeights(agent.weights);
}
public static NNAgent Mutate(NNAgent agent, float probability, float amount)
{
NNAgent mutate = new NNAgent(agent);
for (int i = 1; i < mutate.layers.Length; i++)
{
for (int j = 0; j < mutate.layers[i]; j++)
{
for (int k = 0; k < mutate.layers[i - 1]; k++)
{
if (UnityEngine.Random.Range(0, 1) < probability)
{
mutate.weights[i - 1][j][k] = UnityEngine.Random.Range(0f, 1f) * (amount * 2.0f) - amount;
}
}
}
}
return mutate;
}
public static NNAgent Crossover(NNAgent agentL, NNAgent agentR, float uniformRate)
{
NNAgent agent = new NNAgent(agentL);
for (int i = 1; i < agent.layers.Length; i++)
{
for (int j = 0; j < agent.layers[i]; j++)
{
for (int k = 0; k < agent.neurons[i - 1].Length; k++)
{
if (UnityEngine.Random.Range(0, 1) > uniformRate)
{
agent.weights[i - 1][j][k] = agentR.weights[i - 1][j][k];
}
}
}
}
return agent;
}
private void GenerateAgents()
{
_generation++;
if (_generation == 0)
{
agents = new NNAgent[spawned.Length];
for (int i = 0; i < agents.Length; i++)
{
agents[i] = new NNAgent(layers, bias);
}
}
else
{
AddFitnessToChart();
NNAgent[] elitAgents = spawned.OrderByDescending(car => car.GetComponent <CarControlSystem>().fitness).Take(elitism).Select(car => car.agent).ToArray();
int newIndex = 0;
for (int i = 0; i < elitism; newIndex++, i++)
{
agents[newIndex] = new NNAgent(elitAgents[i]);
}
for (int i = 0; i < mutation; newIndex++, i++)
{
agents[newIndex] = new NNAgent(elitAgents[i % 5]);
agents[newIndex].Mutator(mutationNeuronProb, mutationWeightProb);
}
for (int i = 0; i < crossover; newIndex++, i++)
{
agents[newIndex] = NNAgent.Crossover(elitAgents[0], elitAgents[(i + 1) % 2], uniformRate);
}
for (int i = 0; i < random; newIndex++, i++)
{
agents[newIndex] = new NNAgent(layers, bias);
}
}
}
private static void testWeights(Dictionary <string, CardClass> classMap, Dictionary <string, List <Card> > deckMap, List <string> deckList, List <double> weights)
{
Console.WriteLine("Simulate Games");
Random r = new Random();
double wins = 0.0;
double losses = 0.0;
double numGames = 3000;
for (int i = 0; i < numGames; i++)
{
string p1Deck = deckList[r.Next(deckList.Count)];
string p2Deck = deckList[r.Next(deckList.Count)];
var gameConfig = new GameConfig()
{
StartPlayer = r.Next(2) + 1,
Player1HeroClass = classMap.GetValueOrDefault(p1Deck, CardClass.MAGE),
Player2HeroClass = classMap.GetValueOrDefault(p2Deck, CardClass.ROGUE),
Player1Deck = deckMap.GetValueOrDefault(p1Deck, Decks.RenoKazakusMage),
Player2Deck = deckMap.GetValueOrDefault(p2Deck, Decks.MiraclePirateRogue),
FillDecks = true,
Shuffle = true,
Logging = false
};
AbstractAgent player1 = new GreedyAgent();
AbstractAgent player2 = new NNAgent(weights);
Console.WriteLine("Game " + i + " " + p1Deck + " " + p2Deck);
var gameHandler = new POGameHandler(gameConfig, player1, player2, repeatDraws: false);
gameHandler.PlayGames(nr_of_games: 1, addResultToGameStats: true, debug: false);
GameStats gameStats = gameHandler.getGameStats();
wins += gameStats.PlayerB_Wins;
losses += gameStats.PlayerA_Wins;
}
Console.WriteLine("Bot winrate: " + (wins / (wins + losses)));
Console.WriteLine("Wins: " + wins);
Console.WriteLine("Losses: " + losses);
Console.WriteLine("Draws: " + (numGames - (wins + losses)));
}
private static void runSimulation(Dictionary <string, CardClass> classMap, Dictionary <string, List <Card> > deckMap, List <string> deckList)
{
int numGames = 3000;
Random r = new Random();
Console.WriteLine("Simulate Games");
List <List <double> > games = new List <List <double> >();
for (int i = 0; i < numGames; i++)
{
double max = 10;
double min = -10;
List <double> randWeights =
Enumerable.Range(0, 24) // create sequence of 100 elements
.Select(_ => r.NextDouble() * (max - min) + min) // for each element select random value
.ToList(); // convert to array.
string p1Deck = deckList[r.Next(deckList.Count)];
string p2Deck = deckList[r.Next(deckList.Count)];
var gameConfig = new GameConfig()
{
StartPlayer = r.Next(2) + 1,
Player1HeroClass = classMap.GetValueOrDefault(p1Deck, CardClass.MAGE),
Player2HeroClass = classMap.GetValueOrDefault(p2Deck, CardClass.ROGUE),
Player1Deck = deckMap.GetValueOrDefault(p1Deck, Decks.RenoKazakusMage),
Player2Deck = deckMap.GetValueOrDefault(p2Deck, Decks.MiraclePirateRogue),
FillDecks = true,
Shuffle = true,
Logging = false
};
AbstractAgent player1 = new RandomAgent();
AbstractAgent player2 = new NNAgent(randWeights);
Console.WriteLine("Game " + i + " " + p1Deck + " " + p2Deck);
var gameHandler = new POGameHandler(gameConfig, player1, player2, repeatDraws: false);
gameHandler.PlayGames(nr_of_games: 1, addResultToGameStats: true, debug: false);
GameStats gameStats = gameHandler.getGameStats();
// gameStats.printResults();
randWeights.Add(gameStats.PlayerB_Wins);
games.Add(randWeights);
// Console.WriteLine(String.Join(",", randWeights.Select(p=>p.ToString()).ToArray()));
}
StringBuilder sb = new StringBuilder();
if (!File.Exists(@"hsdata.csv"))
{
sb.Append("HERO_HEALTH_REDUCED,HERO_ATTACK_REDUCED,WEAPON_DURABILITY_REDUCED,MINION_HEALTH_REDUCED,MINION_ATTACK_REDUCED,MINION_KILLED,MINION_APPEARED,SECRET_REMOVED,MANA_REDUCED,M_HEALTH,M_ATTACK,M_HAS_CHARGE,M_HAS_DEAHTRATTLE,M_HAS_DIVINE_SHIELD,M_HAS_LIFE_STEAL,M_HAS_STEALTH,M_HAS_TAUNT,M_HAS_WINDFURY,M_IS_RUSH,M_MANA_COST,M_POISONOUS,M_SILENCED,M_SUMMONED,M_CANT_BE_TARGETED_BY_SPELLS,RESULT\r\n");
}
for (int i = 0; i < games.Count(); i++)
{
for (int j = 0; j < games[0].Count(); j++)
{
sb.Append((j == 0 ? "" : ",") + games[i][j]);
}
sb.AppendLine();
}
File.AppendAllText(@"hsdata.csv", sb.ToString());
Console.WriteLine("Simulation successful");
Console.ReadLine();
}
