A B C D F G H I J L M N P R S T U

S

SENDER - Static variable in class models.SignalingGame
 
setAgreement(int, int, int) - Method in class models.BiasedNetworkModel
Sets the agreement counter for two agents to a specified value.
setAlpha(double[]) - Method in class utilities.Individual
Sets alpha at a specific value
setAlpha(double, int) - Method in class utilities.Individual
Sets alpha at a specific value
setBeliefs(double[]) - Method in class utilities.Individual
A function to set the Bayesian beliefs for one domain.
setBeliefs(double[][]) - Method in class utilities.Individual
A function to set the Bayesian beliefs for multi-domain situations.
setBeliefs(double[], int) - Method in class utilities.Individual
A function to set the Bayesian beliefs for one domain in mutli-domain learning situations.
setBeta(double) - Method in class learningRules.SmoothReinforcement
Sets the value of beta.
setBeta(double[]) - Method in class utilities.Individual
Sets beta at a specific value
setBeta(double, int) - Method in class utilities.Individual
Sets beta at a specific value
setBigPayoff(int) - Method in class utilities.Game
Sets the biggest possible payoff, and then recalculates the probabilites based on that.
setConnected(HashSet) - Method in class utilities.Individual
Sets the neighbors to a particular HashSet of individuals
setConnectionRule(ConnectionRule) - Method in class utilities.Individual
Sets the connection rule, which determines how the individual updates its neighborhood
setConnectProb(double) - Method in class models.RandomNetworkModel
Sets the connection probability
setConstraint(double) - Method in class utilities.Individual
Sets a constraint that initializations can be constrained by.
setConstraint(double[]) - Method in class utilities.Individual
Sets a constraint that initializations can be constrained by.
setConstraint(int, double) - Method in class utilities.Individual
Sets a constraint that initializations can be constrained by.
setDelay(int) - Method in class utilities.AnimatedGifEncoder
Sets the delay time between each frame, or changes it for subsequent frames (applies to last frame added).
setDelta(double) - Method in class learningRules.SmoothReinforcement
Sets the value of delta.
setDiscount(double) - Method in class utilities.Individual
Sets a discount value
setDispose(int) - Method in class utilities.AnimatedGifEncoder
Sets the GIF frame disposal code for the last added frame and any subsequent frames.
setE(double) - Method in class models.HybridModel
 
setFrameRate(float) - Method in class utilities.AnimatedGifEncoder
Sets frame rate in frames per second.
setGame(Game) - Method in class models.SingleDPL
Sets the value of game.
setGame(Game) - Method in class models.RandomNetworkModel
Sets the value of game.
setGame(Game) - Method in class models.PayoffLearningModel
Sets the value of game.
setGame(Game) - Method in class models.BiasedNetworkModel
Sets the value of game.
setGame(Game) - Method in class utilities.Individual
Sets the game
setGames(Game[]) - Method in class models.StandardModel
Sets an array of games, one for each state of the world.
setGames(Game[]) - Method in class models.SingleBGM
Sets an array of games, one for each state of the world.
setGames(Game[]) - Method in class models.HybridModel
Sets an array of games, one for each state of the world.
setGames(Game[]) - Method in class models.BgModel
Sets an array of games, one for each state of the world.
setId(int) - Method in class utilities.Individual
Sets the id number.
setIndivids(Individual[]) - Method in class models.RandomNetworkModel
Sets the value of indivis.
setIndivids(Individual[]) - Method in class models.PayoffLearningModel
Sets the value of indivis.
setIndivids(Individual[]) - Method in class models.BiasedNetworkModel
Sets the value of indivis.
setIndividual(Individual) - Method in class models.SingleDPL
Sets the value of indivis.
setIndividual(Individual) - Method in class models.SingleBGM
Sets the list of individuals for the model.
setIndividuals(Individual[]) - Method in class models.StandardModel
Sets the list of individuals for the model.
setIndividuals(Individual[]) - Method in class models.SimpleCondorcetModel
Sets the list of individuals for the model.
setIndividuals(Individual[]) - Method in class models.HybridModel
Sets the list of individuals for the model.
setIndividuals(Individual[]) - Method in class models.BgModel
Sets the list of individuals for the model.
setLastPayoff() - Method in class utilities.Individual
Sets the last round payoff equal to the current payoff
setLastStrat() - Method in class utilities.Individual
This updates the strategy for the next round by setting the last round strat equal to the current strat.
setLearningRule(LearningRule) - Method in class utilities.Individual
Sets the learning rule for updating strategies
setMatrix(int[][]) - Method in class utilities.Game
Sets the payoff matrix.
setMatrix(int[][], int) - Method in class utilities.Game
Sets the payoff matrix.
setMaxalpha(int) - Method in class utilities.Individual
Sets the value of maxalpha.
setMaxbeta(int) - Method in class utilities.Individual
Sets the value of maxbeta.
setMaximumProb(double) - Method in class models.BiasedNetworkModel
Sets the connection probability
setMaxWeight(int) - Method in class utilities.Individual
Sets the maxWeight
setMinimumProb(double) - Method in class models.BiasedNetworkModel
Sets the connection probability
setMutation(double) - Method in class utilities.Individual
Calls the mutationRule set function.
setMutationRate(double[][]) - Method in class mutationRules.MutateStrategy
Same as constructor
setMutationRate(double, int) - Method in class mutationRules.NoMutate
Does nothing
setMutationRate(double, int) - Method in interface mutationRules.MutationRule
 
setMutationRate(double, int) - Method in class mutationRules.MutateStrategy
Sets the mutation rate (equivalent to the constructor)
setMutationRate(double, int) - Method in class mutationRules.MutateBeliefs
Sets the mutation rate
setMutationRule(MutationRule) - Method in class utilities.Individual
 
setNeighDiscount(double) - Method in class connectionRules.NeighborReinforce
Sets the neighbor discount rate.
setNetwork(Individual[]) - Method in class utilities.Individual
Sets the network (all other individuals in the model).
setPayoff(int) - Method in class utilities.Individual
Sets the payoff from the last generation
setQuality(int) - Method in class utilities.AnimatedGifEncoder
Sets quality of color quantization (conversion of images to the maximum 256 colors allowed by the GIF specification).
setRandom(MersenneTwister) - Method in class models.StandardModel
Sets the random number generator.
setRandom(MersenneTwister) - Method in class models.SingleBGM
Sets the random number generator.
setRandom(MersenneTwister) - Method in class models.SimpleCondorcetModel
Sets the random number generator.
setRandom(MersenneTwister) - Method in class models.HybridModel
Sets the random number generator.
setRandom(MersenneTwister) - Method in class models.BgModel
Sets the random number generator.
setRandom(MersenneTwister) - Method in class utilities.Individual
Sets the random number generator
setRandom(MersenneTwister) - Method in class utilities.Game
Sets the random number generator
setRepeat(int) - Method in class utilities.AnimatedGifEncoder
Sets the number of times the set of GIF frames should be played.
setSeed(int[]) - Method in class utilities.MersenneTwister
An alternative, more complete, method of seeding the pseudo random number generator.
setSeed(long) - Method in class utilities.MersenneTwister
Initalize the pseudo random number generator.
setSize(int, int) - Method in class utilities.AnimatedGifEncoder
Sets the GIF frame size.
setStochastic(boolean) - Method in class utilities.Game
A function to set if the game is stochastic.
setStrat(int) - Method in class utilities.Individual
Sets the current strategy of a user
setStrategic(boolean) - Method in class utilities.Game
A function to set if the game is strategic.
setStratWeights(double[]) - Method in class utilities.Individual
Sets the strategy weights to a specific value.
setStratWeights(double[][]) - Method in class utilities.Individual
Sets the strategy weights to a specific value.
setStratWeights(int, double) - Method in class utilities.Individual
Sets the strategy weight for a particular strategy to a specific value.
setStratWeights(int, int, double) - Method in class utilities.Individual
Sets the strategy weight for a particular strategy to a specific value.
setTotalPlayed(int) - Method in class models.BiasedNetworkModel
Sets the value of totalPlayed.
setTransparent(Color) - Method in class utilities.AnimatedGifEncoder
Sets the transparent color for the last added frame and any subsequent frames.
SignalingGame - class models.SignalingGame.
 
SignalingGame(int, int, double, double) - Constructor for class models.SignalingGame
Constructor.
SimpleCondorcetModel - class models.SimpleCondorcetModel.
The world is set in state 0, each individual is given (noisy) access to the world.
SimpleCondorcetModel() - Constructor for class models.SimpleCondorcetModel
Does nothing
SimpleCondorcetModel(int) - Constructor for class models.SimpleCondorcetModel
Sets up a group of individuals of size n.
SingleBGM - class models.SingleBGM.
 
SingleBGM(JSAPResult) - Constructor for class models.SingleBGM
 
SingleDPL - class models.SingleDPL.
 
SingleDPL(JSAPResult) - Constructor for class models.SingleDPL
 
SinglePlayerModel - class models.SinglePlayerModel.
This class will run any of the four interesting models with any of three learning rules but only for a single player.
SinglePlayerModel() - Constructor for class models.SinglePlayerModel
 
SingleSM - class models.SingleSM.
 
SingleSM(JSAPResult) - Constructor for class models.SingleSM
 
SingleSPL - class models.SingleSPL.
 
SingleSPL(JSAPResult) - Constructor for class models.SingleSPL
 
SmoothBGLearning - class learningRules.SmoothBGLearning.
This is a strategy learning model for the Bala Goyal Model.
SmoothBGLearning(Game[], double) - Constructor for class learningRules.SmoothBGLearning
Initializing a BgLearning model.
SmoothPayoffLearning - class learningRules.SmoothPayoffLearning.
A learning rule where individuals learn the payoffs in a n-strategy game.
SmoothPayoffLearning(Game, double) - Constructor for class learningRules.SmoothPayoffLearning
 
SmoothReinforcement - class learningRules.SmoothReinforcement.
This implements a modification of the standard reinforcement dynamics.
SmoothReinforcement(double, double) - Constructor for class learningRules.SmoothReinforcement
 
StandardModel - class models.StandardModel.
This is a class that runs the Standard Model of Bayesian Learning in Networks.
StandardModel() - Constructor for class models.StandardModel
Does nothing
StandardModel(int) - Constructor for class models.StandardModel
Creates a new StandardModel with a specified number of individuals.
start(Individual, String) - Method in class utilities.BeliefAnimation
 
start(OutputStream) - Method in class utilities.AnimatedGifEncoder
Initiates GIF file creation on the given stream.
start(String) - Method in class utilities.AnimatedGifEncoder
Initiates writing of a GIF file with the specified name.
StratReinforce - class learningRules.StratReinforce.
Simple reinforcement learning for strategies
StratReinforce(double) - Constructor for class learningRules.StratReinforce
This takes a multiplicative scalling factor so that the weights don't grow extremely large (outside the realm of double)
stringMatrix(String) - Static method in class utilities.GraphIO
A function to turn a string representing an adjacency matrix into an integer matrix.

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