Package org.evoludo.simulator.modules

Class NetGames.IBSPop

Object

IBSPopulation

IBSDPopulation

IBSPop

Enclosing class:

NetGames

public class NetGames.IBSPop
extends IBSDPopulation

The extension for IBS simulations implement cooperative actions on dynamical networks.

Field Summary

Fields

Modifier and Type	Field	Description
(package private) double	meanPerformance	The mean fitness of individuals.
(package private) double[]	performance	The array with the mean, minimum, and maximum fitness of individuals.
(package private) double	prevgen	The previous generation time.

Fields inherited from class IBSDPopulation

accuTypeScores, active, groupmodule, init, initCount, module, mutation, opponent, optimizeMoran, pairmodule, traitsCount, traitsNext

Fields inherited from class IBSPopulation

adjustScores, competition, compGroup, debugFocal, debugModel, debugModels, debugNModels, debugSame, distrMigrants, engine, fitness, groupScores, hasLookupTable, interaction, interactions, interGroup, isMultispecies, isNeutral, logger, map2fit, maxEffScoreIdx, maxFitness, maxScore, migrationType, minFitness, minScore, nMixedInter, nPopulation, nTraits, pAddwire, playerScoreAveraged, playerScoring, pMigration, pRewire, rng, scores, smallScores, staticmodule, sumFitness, tags, typeFitness, typeScores, VACANT

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	IBSPop(EvoLudo engine, NetGames module)	Create a new instance of the IBS model for cooperative actions on dynamical networks.

Method Summary

Modifier and Type	Method	Description
protected boolean	addCandidate(int focal, int mdl)	The focal individual with index focal considers acts of cooperation towards the candidate member with index mdl through a probabilistic comparison of their differences in fitness as well as in levels of cooperativity.
boolean	checkGeometry(Geometry geom)	Provide opportunity/hook for subclasses to introduce new geometries.
void	commitTraitAt(int index)	The change of a trait of the player at index is stored in a temporary variable and must be committed before proceeding.
void	commitTraits()	After a synchronous update step the new state must be copied back to become the current state.
boolean	generateGeometry(Geometry geom)	Provide opportunity/hook for subclasses to introduce new geometries.
protected double	getCooperativityDiff(int focal, int mdl)	Calculate the difference in cooperativity of individual index focal as compared to the model individual with index mdl.
<T> void	getFitnessData(T[] colors, ColorMap.Gradient1D<T> cMap)	Returns the fitness of all individuals in this population coded as colors in the array colors using the map colorMap.
protected double	getFitnessDiff(int focal, int mdl)	Calculate the difference in fitness of individual with index focal as compared to the model individual with index mdl.
void	getFitnessHistogramData(double[][] bins)	Generates a histogram of the fitness distribution in this population.
int	getInteractionsAt(int idx)	Gets the number of interactions of the individual with index idx.
private <T> T	getLeafColor(T type, ColorMap<T> cMap)	Utility method to determine the color of leaves in the network.
void	getMeanFitness(double[] meanscores)	Returns the mean fitness of this population in the array mean.
void	getMeanTraits(double[] mean)	Returns the mean trait(s) of this population in the array mean.
protected double	getProbability(double z)	Converts the difference z into a probability following the Fermi function \[p = 1/(1+\exp(-w z)),\] where \(w\) denotes the selection strength.
String	getStatus()	Gets the status of the as a formatted string.
String	getTagNameAt(int idx)	Gets the formatted tag of the individual with index idx as string.
<T> void	getTraitData(T[] colors, ColorMap<T> cMap)	Returns the traits of all individuals in this population coded as colors in the array colors using the map colorMap.
String	getTraitNameAt(int index)	Gets the formatted name of the trait of the individual at site index.
boolean	haveSameTrait(int a, int b)	Check if individuals with index a and index b have the same traits.
void	init()	Initialize the model.
boolean	isSameTrait(int a)	Check if individual with index a has switched traits.
boolean	parseGeometry(Geometry geom, String arg)	Provide opportunity/hook for subclasses to introduce new geometries.
void	playGameSyncAt(int idx)	Update the score of individual me.
void	playGroupGameAt(IBSGroup group)	Play a group interaction with the individuals in group.
void	playPairGameAt(IBSGroup group)	Play a pairwise interaction with the individuals in group.
boolean	preferredPlayerBest(int me, int best, int sample)	For deterministic updating with multiple traits (more than two), it must be specified which trait is the preferred one.
void	prepareTraits()	Prior to a synchronous update step the current state must be duplicated in preparation for processing the next step.
protected boolean	removeCandidate(int focal, int mdl)	The focal individual with index focal considers to stop acts of cooperation towards the candidate member with index mdl through a probabilistic comparison of their differences in fitness as well as in levels of cooperativity.
void	reset()	Reset the model.
void	resetScores()	Reset scores and fitness of all individuals to zero.
void	resetTraits()	Reset all traits in preparation of the next update step.
int	step()	Perform a single IBS step, i.e.
void	swapTraits(int a, int b)	Swap traits of individuals with index a and index b.
void	updateFitnessMean()	Update the mean, minimum, and maximum fitness of individuals.
boolean	updatePlayerBestResponse(int index, int[] group, int size)	Best-response update.
protected void	updatePlayerIndividual(int focal)	Update the focal individual with index focal by probabilistically removing links from more successful and less cooperative individuals, adding links to more successful and more cooperative individuals.
void	updateScores()	Update the scores of all individuals in the population.
void	yalpGroupGameAt(IBSGroup groupd)	Counterpart of IBSPopulation.playGroupGameAt(IBSGroup), IBSPopulation.playGameAt(int) and/or IBSPopulation.playGameSyncAt(int).

Methods inherited from class IBSDPopulation

adjustGameScoresAt, adjustPairGameScoresAt, adjustScoreAt, adjustScoreAt, becomesVacantAt, check, checkConvergence, countTraits, debugMarkChange, doAdjustScores, encodeTraits, getFitnessAt, getInit, getInitialTraits, getMonoScore, getPopulationSize, getScoreAt, getTraitAt, getTraits, getTraitsCount, initFrequency, initKaleidoscope, initMono, initMono, initMono, initMutant, initStripes, initTemperature, initUniform, isConsistent, isMonomorphic, isVacantAt, maybeMutateAt, maybeMutateMoran, mouseHitNode, mutateAt, resetScoreAt, restoreFitness, restoreTraits, setInit, setInitialTraits, setNextTraitAt, setOpponentPop, setScoreAt, setTraitAt, stripGroupVacancies, stripVacancies, updateFromModelAt, updateMixedMeanScores, updatePlayerEcologyAt, updatePlayerMoranBirthDeath, updatePlayerMoranDeathBirth, updatePlayerMoranDeathBirth, updatePlayerMoranImitate, updateScoreAt, updateTraitCount

Methods inherited from class IBSPopulation

createCompetitionGeometry, createInteractionGeometry, debugScores, debugUpdatePopulationAt, doBirthDeathMigration, doDeathBirthMigration, doDiffusionMigration, doMigration, doSyncMigration, encodeFitness, encodeGeometry, encodeInteractions, getCompetitionGeometry, getCompGroup, getFitness, getFitnessNameAt, getFitnessNameAt, getInteractionGeometry, getInterGroup, getMaxScore, getMigrationProb, getMigrationType, getMinScore, getModule, getNMean, getPlayerScoreAveraged, getPlayerScoring, getPopulationUpdate, getScoreNameAt, getScores, getSpeciesUpdateRate, getSyncFraction, getTagAt, getTagData, getTags, getTotalFitness, migrateMoran, mouseHitNode, mutate, nextBinomial, pickFitFocalIndividual, pickFitFocalIndividual, pickFitNeighborAt, pickFitNeighborAt, pickFocalIndividual, pickFocalIndividual, pickFocalSite, pickFocalSite, pickNeighborSiteAt, playGameAt, processScore, random01, random01d, random0n, random0N, randomGaussian, removeScoreAt, removeScoreAt, restoreGeometry, restoreInteractions, setAddwire, setConsistencyCheck, setMaxEffScoreIdx, setMigrationProb, setMigrationType, setPlayerScoreAveraged, setPlayerScoring, setPopulationUpdate, setRewire, setSyncFraction, setTagAt, srandom, swapScoresAt, updateEffScoreRange, updateFitnessAt, updateMinMaxScores, updatePlayerAsync, updatePlayerAsyncAt, updatePlayerAt, updatePlayerAt, updatePlayerBest, updatePlayerBestHalf, updatePlayerEcology, updatePlayerMoranBirthDeathAt, updatePlayerMoranDeathBirthAt, updatePlayerMoranImitateAt, updatePlayerSwap, updateProportionalAbs, updateReplicatorHalf, updateReplicatorPlus, updateScoreAt, updateScoreAt, updateThermal

Methods inherited from class Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Details

prevgen

double prevgen

The previous generation time.

meanPerformance

double meanPerformance

The mean fitness of individuals.

performance

double[] performance

The array with the mean, minimum, and maximum fitness of individuals.

Constructor Details

IBSPop

protected IBSPop(EvoLudo engine,
 NetGames module)

Create a new instance of the IBS model for cooperative actions on dynamical networks.

Parameters:

engine - the pacemaker for running the model

module - the module that defines the game

Method Details

reset

public void reset()

Description copied from class: IBSDPopulation

Reset the model. All parameters must be consistent at this point. Allocate memory and initialize the interaction and competition structures. If structures include random elements, e.g. random regular graphs, a new structure is generated. Generate initial configuration. Subclasses must override this method to allocate memory for the trait and call super.

Allocates memory for optimized Moran process.

Discussions/extensions

groupScores unused in IBSDPopulation. Merge with traitScore?

Overrides:

reset in class IBSDPopulation

See Also:

• IBSDPopulation.optimizeMoran
• IBSDPopulation.updatePlayerMoranBirthDeath()

init

public void init()

Description copied from class: IBSPopulation

Initialize the model. All parameters must be consistent. Subclasses must override this method to generate the initial trait configuration and call super.

Note: Initialization leaves the interaction and competition structures untouched

Overrides:

init in class IBSDPopulation

See Also:

• IBSPopulation.check()
• Model.init()

getStatus

public String getStatus()

Description copied from class: IBSPopulation

Gets the status of the as a formatted string. This is typically used in the GUI to summarize the progress of the model.

Overrides:

getStatus in class IBSDPopulation

Returns:

the status of the population

step

public int step()

Description copied from class: IBSPopulation

Perform a single IBS step, i.e. update one individual for asynchronous updates or once the entire population for synchronous updates.

Discussions/extensions

1. Review migration. Exclusively used in Demes2x2. Should probably be treated as an independent event, in particular independent of population or player updates
2. Implement Wright-Fisher update.
3. How to scale realtime with multiple populations? How to define a generation if population sizes can vary?
4. IBSPopulation.updatePlayerEcology() returns time increment in realtime units. Everyone else does fine without...

Overrides:

step in class IBSPopulation

Returns:

the number of elapsed realtime units

updatePlayerIndividual

protected void updatePlayerIndividual(int focal)

Update the focal individual with index focal by probabilistically

1. removing links from more successful and less cooperative individuals,
2. adding links to more successful and more cooperative individuals.

Parameters:

focal - the index of the individual to be updated

See Also:

• removeCandidate(int, int)
• addCandidate(int, int)

addCandidate

protected boolean addCandidate(int focal,
 int mdl)

The focal individual with index focal considers acts of cooperation towards the candidate member with index mdl through a probabilistic comparison of their differences in fitness as well as in levels of cooperativity. Links are more likely established to more successful and more cooperative individuals.

Parameters:

focal - the index of the focal individual

mdl - the index of the candidate member

Returns:

true to establish the direct link from focal to mdl

See Also:

• getFitnessDiff(int, int)
• getCooperativityDiff(int, int)
• getProbability(double)

removeCandidate

protected boolean removeCandidate(int focal,
 int mdl)

The focal individual with index focal considers to stop acts of cooperation towards the candidate member with index mdl through a probabilistic comparison of their differences in fitness as well as in levels of cooperativity. Links to more successful and less cooperative individuals are more likely removed.

Parameters:

focal - the index of the focal individual

mdl - the index of the candidate member

Returns:

true to remove the direct link from focal to mdl

getFitnessDiff

protected double getFitnessDiff(int focal,
 int mdl)

Calculate the difference in fitness of individual with index focal as compared to the model individual with index mdl. The fitness difference is normalized to [-1,1] where negative differences refer to models that do worse and positive ones to models that perform better.

Parameters:

focal - the index of the focal individual

mdl - the index of the candidate member

Returns:

the normalized difference in fitness

getCooperativityDiff

protected double getCooperativityDiff(int focal,
 int mdl)

Calculate the difference in cooperativity of individual index focal as compared to the model individual with index mdl. The cooperativity difference is normalized to [-1,1] where negative differences refer to models that are less cooperative and positive ones to models that are more cooperative.

Parameters:

focal - the index of the focal individual

mdl - the index of the candidate member

Returns:

the normalized difference in cooperativity

getProbability

protected double getProbability(double z)

Converts the difference z into a probability following the Fermi function \[p = 1/(1+\exp(-w z)),\] where \(w\) denotes the selection strength.

Parameters:

z - the difference to convert into a probability

Returns:

the probability

updateFitnessMean

public void updateFitnessMean()

Update the mean, minimum, and maximum fitness of individuals.

getMeanTraits

public void getMeanTraits(double[] mean)

Description copied from class: IBSPopulation

Returns the mean trait(s) of this population in the array mean. Used by GUI to visualize the current state of this IBS model.

Overrides:

getMeanTraits in class IBSDPopulation

Parameters:

mean - the array for returning the trait values

See Also:

• Model.getMeanTraits(int, double[])

getMeanFitness

public void getMeanFitness(double[] meanscores)

Description copied from class: IBSPopulation

Returns the mean fitness of this population in the array mean. Used by GUI to visualize the current state of this IBS model. Returns true if data point belongs to the same time series and false if a new series was started through IBSPopulation.init() or IBSPopulation.reset().

Overrides:

getMeanFitness in class IBSDPopulation

Parameters:

meanscores - the array for storing the mean fitness values

See Also:

• Model.getMeanFitness(int, double[])

getFitnessData

public <T> void getFitnessData(T[] colors,
 ColorMap.Gradient1D<T> cMap)

Description copied from class: IBSPopulation

Returns the fitness of all individuals in this population coded as colors in the array colors using the map colorMap. Used by GUI to visualize the current state of this IBS model. Colors are coded in different data types <T> depending on the runtime environment (GWT or JRE) as well as the graph (e.g. PopGraph2D or PopGraph3D).

Overrides:

getFitnessData in class IBSPopulation

Type Parameters:

T - the type of color data (String or MeshLambertMaterial for GWT and Color for JRE).

Parameters:

colors - the array where the colors of all nodes are stored

cMap - the map that converts traits into colors

getLeafColor

private <T> T getLeafColor(T type,
 ColorMap<T> cMap)

Utility method to determine the color of leaves in the network.

Type Parameters:

T - the type parameter of the color

Parameters:

type - the type of color to use

cMap - the color map to use

Returns:

the color of the leaf with type T

getFitnessHistogramData

public void getFitnessHistogramData(double[][] bins)

Description copied from class: IBSPopulation

Generates a histogram of the fitness distribution in this population. The result is returned in the array bins.

Notes:

1. bins is a 2D array because discrete models generate histograms for each trait separately.
2. By default generate a histogram of the scores in bins[0].
3. Consider moving to IBSDPopulation and IBSCPopulation with arguments bins[][] and bins[], respectively.

Overrides:

getFitnessHistogramData in class IBSDPopulation

Parameters:

bins - the 2D array to store the histogram(s)

parseGeometry

public boolean parseGeometry(Geometry geom,
 String arg)

Description copied from class: IBSPopulation

Provide opportunity/hook for subclasses to introduce new geometries.

Overrides:

parseGeometry in class IBSPopulation

Parameters:

geom - the current empty/uninitialized geometry

arg - the commandline argument

Returns:

true if parsing was successful

See Also:

• Geometry.parse(String)

checkGeometry

public boolean checkGeometry(Geometry geom)

Description copied from class: IBSPopulation

Provide opportunity/hook for subclasses to introduce new geometries.

Overrides:

checkGeometry in class IBSPopulation

Parameters:

geom - the geometry to check

Returns:

true if checks were successful

See Also:

• Geometry.check()

generateGeometry

public boolean generateGeometry(Geometry geom)

Description copied from class: IBSPopulation

Provide opportunity/hook for subclasses to introduce new geometries.

Overrides:

generateGeometry in class IBSPopulation

Parameters:

geom - the geometry to initialize

Returns:

true if generation of structure was successful

See Also:

• Geometry.init()

resetScores

public void resetScores()

Description copied from class: IBSPopulation

Reset scores and fitness of all individuals to zero.

Overrides:

resetScores in class IBSDPopulation

updateScores

public void updateScores()

Description copied from class: IBSDPopulation

Update the scores of all individuals in the population.

Note: Overridden to set scores in well-mixed populations more efficiently.

Overrides:

updateScores in class IBSDPopulation

resetTraits

public void resetTraits()

Description copied from class: IBSDPopulation

Reset all traits in preparation of the next update step. Simply an opportunity for customizations in subclasses.

Reset the colors of recently changed trait.

Overrides:

resetTraits in class IBSDPopulation

prepareTraits

public void prepareTraits()

Description copied from class: IBSPopulation

Prior to a synchronous update step the current state must be duplicated in preparation for processing the next step.

Overrides:

prepareTraits in class IBSDPopulation

See Also:

• IBSPopulation.commitTraits()

commitTraits

public void commitTraits()

Description copied from class: IBSDPopulation

After a synchronous update step the new state must be copied back to become the current state.

For discrete modules, update the trait count of each type and check if population reached a homogeneous state.

Overrides:

commitTraits in class IBSDPopulation

See Also:

• IBSPopulation.prepareTraits()

commitTraitAt

public void commitTraitAt(int index)

Description copied from class: IBSPopulation

The change of a trait of the player at index is stored in a temporary variable and must be committed before proceeding.

Overrides:

commitTraitAt in class IBSDPopulation

Parameters:

index - the index of the player that needs to have its new trait committed

haveSameTrait

public boolean haveSameTrait(int a,
 int b)

Description copied from class: IBSPopulation

Check if individuals with index a and index b have the same traits.

Overrides:

haveSameTrait in class IBSDPopulation

Parameters:

a - the index of first individual

b - the index of second individual

Returns:

true if the two individuals have the same traits

isSameTrait

public boolean isSameTrait(int a)

Description copied from class: IBSPopulation

Check if individual with index a has switched traits.

Note: this test is only meaningful before trait are committed.

Overrides:

isSameTrait in class IBSDPopulation

Parameters:

a - index of individual

Returns:

true if trait remained unchanged

See Also:

• IBSPopulation.commitTraitAt(int)

swapTraits

public void swapTraits(int a,
 int b)

Description copied from class: IBSPopulation

Swap traits of individuals with index a and index b.

Note: the traits still need to be committed.

Overrides:

swapTraits in class IBSDPopulation

Parameters:

a - the index of first individual

b - the index of second individual

See Also:

• IBSPopulation.commitTraitAt(int)

playPairGameAt

public void playPairGameAt(IBSGroup group)

Description copied from class: IBSPopulation

Play a pairwise interaction with the individuals in group.

Overrides:

playPairGameAt in class IBSDPopulation

Parameters:

group - the group of individuals interacting in pairs

playGroupGameAt

public void playGroupGameAt(IBSGroup group)

Description copied from class: IBSPopulation

Play a group interaction with the individuals in group.

Overrides:

playGroupGameAt in class IBSDPopulation

Parameters:

group - the group of interacting individuals

playGameSyncAt

public void playGameSyncAt(int idx)

Description copied from class: IBSPopulation

Update the score of individual me.

After initialization and for synchronized population updating this method is invoked (rather than IBSPopulation.playGameAt(int)). The synchronous flag simply indicates that all players are going to be updated. For directed graphs this implies that incoming and outgoing links do not need to be treated separately because every outgoing link corresponds to an incoming link of another node.

Overrides:

playGameSyncAt in class IBSPopulation

Parameters:

idx - the index of the focal individual

yalpGroupGameAt

public void yalpGroupGameAt(IBSGroup groupd)

Description copied from class: IBSPopulation

Counterpart of IBSPopulation.playGroupGameAt(IBSGroup), IBSPopulation.playGameAt(int) and/or IBSPopulation.playGameSyncAt(int). Removes the payoffs of group interactions.

Overrides:

yalpGroupGameAt in class IBSDPopulation

Parameters:

groupd - the interaction group

updatePlayerBestResponse

public boolean updatePlayerBestResponse(int index,
 int[] group,
 int size)

Description copied from class: IBSDPopulation

Best-response update.

Important:

1. The array group is untouchable because it may refer to the population structure. Any change would also permanently change the structure.
2. The best-response update must be implemented in subclasses that override this method. By default throws an error.
3. Instead of overriding the method, subclasses may remove PlayerUpdate.Type.BEST_RESPONSE from PlayerUpdate#clo.

Note: Takes composition of entire population into account for Geometry.Type#MEANFIELD but only the reference neighborhood in structured populations.

Overrides:

updatePlayerBestResponse in class IBSDPopulation

Parameters:

index - the index of individual to update

group - the array with indices of reference group

size - the size of the reference group

Returns:

true if trait changed (signaling score needs to be reset)

preferredPlayerBest

public boolean preferredPlayerBest(int me,
 int best,
 int sample)

Description copied from class: IBSDPopulation

For deterministic updating with multiple traits (more than two), it must be specified which trait is the preferred one.

Summary: does 'me' prefer 'sample' over 'best'?

Here we introduce the convention of a cyclic preference where traits with lower indices are always preferred. For example, with N traits, trait 0 is preferred over 1 preferred over 2... preferred over N-1 preferred over N preferred over 0, etc. This convention is arbitrary but makes sense for systems with cyclic dominance of traits and such systems are most likely to produce evolutionary kaleidoscopes and only for those is this deterministic updating of crucial importance. For anything else, these are irrelevant quibbles.

Overrides:

preferredPlayerBest in class IBSDPopulation

Parameters:

me - the index of the focal individual

best - the index of the best performing individual

sample - the index of the sample type

Returns:

true if sample is preferred over best

getTraitNameAt

public String getTraitNameAt(int index)

Description copied from class: IBSPopulation

Gets the formatted name of the trait of the individual at site index.

Overrides:

getTraitNameAt in class IBSDPopulation

Parameters:

index - the index of the

Returns:

the string describing the trait

getInteractionsAt

public int getInteractionsAt(int idx)

Description copied from class: IBSPopulation

Gets the number of interactions of the individual with index idx. Returns -1 if site idx is vacant or fitness is static, i.e. not based on interactions.

Overrides:

getInteractionsAt in class IBSPopulation

Parameters:

idx - the index of the individual

Returns:

the number of interactions

getTagNameAt

public String getTagNameAt(int idx)

Description copied from class: IBSPopulation

Gets the formatted tag of the individual with index idx as string.

Overrides:

getTagNameAt in class IBSPopulation

Parameters:

idx - the index of the individual

Returns:

the tag as a string

getTraitData

public <T> void getTraitData(T[] colors,
 ColorMap<T> cMap)

Returns the traits of all individuals in this population coded as colors in the array colors using the map colorMap. Used by GUI to visualize the current state of this IBS model. Colors are coded in different data types <T> depending on the runtime environment (GWT or JRE) as well as the graph (e.g. PopGraph2D or PopGraph3D).

Note: with the help of engine (see EvoLudoGWT and EvoLudoJRE) the color specifics of GWT and JRE are shielded from interfering with shared code. Some careful checks and casts are needed to ensure the correct color map is used while preventing re-allocation of the custom color gradients.

Overrides:

getTraitData in class IBSDPopulation

Type Parameters:

T - the type of color data (String or MeshLambertMaterial for GWT and Color for JRE).

Parameters:

colors - the array where the colors of all nodes are stored

cMap - the map that converts traits into colors