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java.lang.Object | +--learningRules.SmoothReinforcement
This implements a modification of the standard reinforcement dynamics.
Constructor Summary | |
SmoothReinforcement(double d,
double b)
|
Method Summary | |
double |
getBeta()
Returns the value of beta. |
double |
getDelta()
Returns the value of delta. |
void |
newGeneration(Individual i)
Prepares the individual for a new generation. |
int |
pickStrat(Individual i)
Picks a strategy based on a logisitic response rule similar to smoothed fictitious play this is for multi domain models |
int |
pickStrat(Individual i,
int d)
Picks a strategy based on a logisitic response rule similar to smoothed fictitious play this is for signaling games |
static double |
probs(double[] x)
This calculates 1/(e^x[0]+e^x[1]+...+e^x[n]) It returns a double which is a rounded version of the result |
void |
processPayoff(Individual i)
Processes the payoff by adding the payoff to the weight of the strategy choosen on this round |
void |
processPayoff(Individual i,
int d)
Processes the payoff by adding the payoff to the weight of the strategy choosen on this round. |
void |
setBeta(double beta)
Sets the value of beta. |
void |
setDelta(double delta)
Sets the value of delta. |
Methods inherited from class java.lang.Object |
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
public SmoothReinforcement(double d, double b)
Method Detail |
public static final double probs(double[] x)
x
- The list of exponents
public double getDelta()
public void setDelta(double delta)
delta
- The value to assign delta.public double getBeta()
public void setBeta(double beta)
beta
- The value to assign beta.public void newGeneration(Individual i) throws ModelError
newGeneration
in interface LearningRule
i
- The calling individual
ModelError
public void processPayoff(Individual i) throws ModelError
processPayoff
in interface LearningRule
i
- The calling individual
ModelError
public void processPayoff(Individual i, int d) throws ModelError
i
- The calling individual
ModelError
public int pickStrat(Individual i)
pickStrat
in interface LearningRule
i
- The calling individualpublic int pickStrat(Individual i, int d)
i
- The calling individual
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