Finds the weak Nash equilibirium for DataBots in one epoch(Radius), requires the
setting of constants, grid, and so on in Pswarm
PswarmCurrentRadiusC2botsPositive( AllDataBotsPosOld, Radius, DataDists,
IndPossibleDBPosR, RadiusPositionsschablone, pp, Nullpunkt, Lines, Columns,
nBots, limit, steigungsverlaufind, StressConstAditiv, debug)list of
ComplexVector, indizes of DataBot Positions after a weak Nash equlibrium is found
NumericVector, intern result, for debugging only
NumericVector, intern result, for debugging only
ComplexVector [1:n,1], DataBots position in the last Nash-Equlibriuum
double, Radius of payoff function, neighborhood, where other DatsBots can be smelled
NumericMatrix, Inputdistances[1:n,1:n]
ComplexVector, see output of
findPossiblePositionsCsingle
NumericMatrix, see AllallowedDBPosR0 in
setPolarGrid
NumericVector, number of jumping simultaneously DataBots of one epoch (per nash-equilibirum), this vector is linearly monotonically decreasing
NumericVector, equals
which(AllallowedDBPosR0==0,arr.ind=T), see see AllallowedDBPosR0
in setPolarGrid
double, small edge length of rectangulare grid
double, big edge length of rectangulare grid
double, intern constant, equals round(pp[Radius]*DBAnzahl)
int, intern constant, equals ceiling(1/pp[Radius])
int, intern constant
double, intern constant, sum of payoff of all databots in random condition before the algorithm starts
optional, bool: If TRUE prints status every 100 iterations
Michael Thrun
Algorithm is described in [Thrun, 2018, p. 95, Listing 8.1].
[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, tools:::Rd_expr_doi("10.1007/978-3-658-20540-9"), 2018.