public static TyStateWeights GetDefault()
{
TyStateWeights p = new TyStateWeights(1.0f);
p.SetWeight(WeightType.HealthFactor, 8.7f);
return(p);
}
public TyStateWeights(TyStateWeights other)
: this()
{
for (int i = 0; i < _weights.Length; i++)
{
_weights[i] = other._weights[i];
}
}
public static TyStateWeights operator -(TyStateWeights lhs, TyStateWeights rhs)
{
TyStateWeights p = new TyStateWeights();
for (int i = 0; i < p._weights.Length; i++)
{
p._weights[i] = lhs._weights[i] - rhs._weights[i];
}
return(p);
}
public static TyStateWeights operator /(TyStateWeights lhs, float rhs)
{
TyStateWeights p = new TyStateWeights();
for (int i = 0; i < p._weights.Length; i++)
{
p._weights[i] = lhs._weights[i] / rhs;
}
return(p);
}
public static TyStateWeights UniformLerp(TyStateWeights lhs, TyStateWeights rhs, float t)
{
TyStateWeights p = new TyStateWeights();
for (int i = 0; i < p._weights.Length; i++)
{
p._weights[i] = TyUtility.Lerp(lhs._weights[i], rhs._weights[i], t);
}
return(p);
}
private TycheAgentCompetition(TyStateWeights weights, bool heroBasedWeights, int episodeMultiplier, bool adjustEpisodeMultiplier)
{
_defaultEpisodeMultiplier = episodeMultiplier;
_curEpisodeMultiplier = episodeMultiplier;
_heroBasedWeights = heroBasedWeights;
_analyzer = new TyStateAnalyzer(weights);
_simTree = new TySimTree();
_random = new Random();
AdjustEpisodeMultiplier = adjustEpisodeMultiplier;
}
/// <summary> Called the first round (might be second round game wise) this agents is able to see the game and his opponent. </summary>
private void CustomInit(POGame.POGame initialState)
{
_hasInitialized = true;
_playerId = initialState.CurrentPlayer.PlayerId;
_analyzer.OwnPlayerId = _playerId;
if (_heroBasedWeights)
{
_analyzer.Weights = TyStateWeights.GetHeroBased(initialState.CurrentPlayer.HeroClass, initialState.CurrentOpponent.HeroClass);
}
}
public static TyStateWeights UniformRandLerp(TyStateWeights lhs, TyStateWeights rhs, System.Random random, float tMin, float tMax)
{
TyStateWeights p = new TyStateWeights();
for (int i = 0; i < p._weights.Length; i++)
{
float t = random.RandFloat(tMin, tMax);
p._weights[i] = TyUtility.Lerp(lhs._weights[i], rhs._weights[i], t);
}
return(p);
}
public static TyStateWeights NonUniformLerp(TyStateWeights lhs, TyStateWeights rhs, float[] tValues)
{
System.Diagnostics.Debug.Assert(tValues.Length >= (int)WeightType.Count);
TyStateWeights p = new TyStateWeights();
for (int i = 0; i < p._weights.Length; i++)
{
p._weights[i] = TyUtility.Lerp(lhs._weights[i], rhs._weights[i], tValues[i]);
}
return(p);
}
public static TycheAgentCompetition GetTrainingAgent(float biasFactor = -1.0f, bool useSecrets = false)
{
const bool ADJUST_EPISODES = false;
const bool HERO_BASED_WEIGHTS = false;
var weights = TyStateWeights.GetDefault();
if (biasFactor >= 0.0f)
{
weights.SetWeight(TyStateWeights.WeightType.BiasFactor, biasFactor);
}
var agent = new TycheAgentCompetition(weights, HERO_BASED_WEIGHTS, 0, ADJUST_EPISODES);
agent.UsedAlgorithm = Algorithm.Greedy;
agent._analyzer.EstimateSecretsAndSpells = useSecrets;
return(agent);
}
public TycheAgentCompetition(double time)
: this(TyStateWeights.GetDefault(), true, DEFAULT_NUM_EPISODES_MULTIPLIER, true)
{
MAX_TIME = time;
}
public static TycheAgentCompetition GetSearchTreeAgent(int episodeMultiplier)
{
return(new TycheAgentCompetition(TyStateWeights.GetDefault(), true, episodeMultiplier, true));
}
public static TycheAgentCompetition GetLearningAgent(TyStateWeights weights)
{
return(new TycheAgentCompetition(weights, false, LEARNING_NUM_EPISODES_MULTIPLIER, false));
}
public TyStateAnalyzer(TyStateWeights weights)
{
Weights = weights;
}
