PswarmRadiusSequential {DatabionicSwarm}

intern function, do not use yourself

Description

Finds the weak Nash equilibirium for DataBots in one epoch(Radius), requires the setting of constants, grid, and so on in Pswarm

Usage

PswarmRadiusSequential( AllDataBotsPosOld, Radius, DataDists,
IndPossibleDBPosR, RadiusPositionsschablone, pp, Nullpunkt, Lines, Columns,
nBots, limit, steigungsverlaufind, Happiness, debug)

Arguments

AllDataBotsPosOld

ComplexVector [1:n,1], DataBots position in the last Nash-Equlibriuum

Radius

double, Radius of payoff function, neighborhood, where other DatsBots can be smelled

DataDists

NumericMatrix, Inputdistances[1:n,1:n]

IndPossibleDBPosR

ComplexVector, see output of findPossiblePositionsCsingle

RadiusPositionsschablone

NumericMatrix, see AllallowedDBPosR0 in setPolarGrid

pp

NumericVector, number of jumping simultaneously DataBots of one eppoch (per nash-equilibirum), this vector is linearly monotonically decreasing

Nullpunkt

NumericVector, equals which(AllallowedDBPosR0==0,arr.ind=T), see see AllallowedDBPosR0 in setPolarGrid

Lines

double, small edge length of rectangulare grid

Columns

double, big edge length of rectangulare grid

nBots

double, intern constant, equals round(pp[Radius]*DBAnzahl)

limit

int, intern constant, equals ceiling(1/pp[Radius])

steigungsverlaufind

int, intern constant

Happiness

double, intern constant, sum of payoff of all databots in random condition before the algorithm starts

debug

optional, bool: If TRUE prints status every 100 iterations

Details

Algorithm is described in [Thrun, 2018, p. 95, Listing 8.1].

Value

list of

AllDataBotsPos

ComplexVector, indizes of DataBot Positions after a weak Nash equlibrium is found

stressverlauf

NumericVector, intern result, for debugging only

fokussiertlaufind

NumericVector, intern result, for debugging only

Author(s)

Michael Thrun

References

[Thrun, 2018] Thrun, M. C.: Projection Based Clustering through Self-Organization and Swarm Intelligence, doctoral dissertation 2017, Springer, Heidelberg, ISBN: 978-3-658-20539-3, doi:10.1007/978-3-658-20540-9, 2018.